LHCb Software Training: Printing and Job options

The purpose of this exercise is to make you familiar with using job options to configure algorithms, and with the methods for printing from within a Gaudi application.

Prerequisites

The instructions assume that you have already followed part 1 of the LHCb software basics tutorial. You should also have looked at the slides "Introduction to Gaudi" [ .ppt] and "Printing and job options" [.ppt] attached to this topic. Please feel free to update these slides if you modify them for a future tutorial session.

These instructions have last been checked against the DaVinci v29r0 environment. Please use this version of DaVinci or a more recent version.

Setting up the environment

We will be working in the same environment as the DaVinci tutorial.

  • Start Eclipse as described in the first tutorial
  • Create a local DaVinci project with using version v29r0 (refer to Exercise 3)
  • Check out the Tutorial/Analysis package (from the Analysis project), version v10r2 using the GetPack Wizard

This package contains a requirements file already set up for the tutorial, a set of options and solutions for the DaVinci tutorial sessions, and an empty src directory

Tip, idea To exploit the full power of the Eclipse C++ editor, you need to ensure that it index is correctly populated (it is not mandatory for the success of this hands-on).

  • For new projects it is very useful to enable the automatic discovery of include directories (it should be enable by default, but for the moment you have to do it by hand)
    • right-click on the new project, select Properties in the menu, find the entry Discovery Options in the menu on the left and check the checkbox Automate discovery of path and symbols
    • build once the project to let Eclipse collect the paths
  • After the update of the paths, the index of classes and files may not be up-to-date
    • right-click on the project, and select Index->Rebuild

Creating a GaudiAlgorithm, adding a property and printing its value

  • Click with the right button on the directory DaVinci_v29r0/Tutorial/Analysis/src the Project Explorer view and select New->LHCb Component in the menu
  • Type MyFirstAlgorithm in the Name field and select Gaudi Algorithm for the Type, then click on Finish
    createAlg-1.png
    LHCb Component wizard
  • Open the file MyFirstAlgorithm.h which has been created in the src directory and add a member variable to store the property
    double m_jPsiMassWin;
  • Open the file MyFirstAlgorithm.cpp
  • In the class constructor, declare a name for the property, initialize it to a default value and document it
    declareProperty( "MassWindow", <memberVariable> = <defaultValue>, "Documentation" );
  • Print the property's value twice, using two different units
    info() << "Mass window is " << value << " Units" << endmsg;
  • Save both files and build the project

Setting up the job options and running the job

  • Create a job options file called myJob.py (right-click on DaVinci_v29r0/Tutorial/Analysis/options, then New->File)
    createAlg-2.png
    New option file
Note
you may be asked to configure the python interpreter, for the moment you can select the automatic configuration and the defaults.
  • Tell python about the Gaudi framework
    from Gaudi.Configuration import *
  • Tell python about your algorithm
    from Configurables import MyFirstAlgorithm
  • Add an instance of your algorithm to the application
    myAlg = MyFirstAlgorithm()
    ApplicationMgr().TopAlg += [myAlg]
  • Save the file and run the job (see either Exercise 4 or Exercise 6 in part 1 of the tutorial). You should see some printout from your algorithm. If you do not, either your algorithm was not called (check your job options) or you put the printout in the wrong place in the code. Only printout from initialize() will be seen; execute() is not called in this example (why?)

Modify the job behavior by changing job options

The following examples illustrate how you can change an algorithm's behaviour by changing the job options, without recompiling. Try the following in turn, rerunning the job each time. No need to recompile!
  • Modify the value of the algorithm's property
    from GaudiKernel.SystemOfUnits import GeV, MeV
    myAlg.MassWindow  = 1.3 * GeV
  • One big advantage of using Python for job options is its syntax and type checking. See what happens with each of the following typing errors:
    myAlg = MyFirstAlgorithm()
    myAlg.MassWindow = 1.3 * GeV
    myAlg.MassWindow = "some string"
  • Change the global output level of the application
    MessageSvc().OutputLevel = DEBUG
    Try any of the values VERBOSE, DEBUG, INFO, WARNING, ERROR
  • Change the output level of your algorithm
    myAlg.OutputLevel = DEBUG
    Try any of the values VERBOSE, DEBUG, INFO, WARNING, ERROR
  • Run two instances of your algorithm, with different values for the cut. Hint:
    anAlg = SomeAlg("Alg1") #instantiates class SomeAlg with instance name "Alg1" and assigns it to python variable anAlg
  • A more detailed discussion of python configurables, including examples for configuring tools, can be found in the TupleToolsAndConfigurables FAQ.

Modify the job behaviour with StatusCode

  • Look at what happens when you change the initialize() method of your algorithm to
    return StatusCode::FAILURE

The LHCb convention is that algorithms should return StatusCode::FAILURE from initialize() if there is a fatal configuration error which makes it pointless to continue with the job. Algorithms should never return StatusCode::FAILURE from inside the event loop ( execute() method), because this will not just stop processing the current event, but will stop the job. Instead, they should trap the error and take any necessary remedial action. There are ways for algorithms to abort processing of the current event only, but these are beyond the scope of this tutorial; detailed instructions are available here

  • Play with the Warning() and Error() methods.
    • What is the difference compared to using the warning() and err() MsgStream functions?.
    • What happens if you
      return Error("An error");
      from your algorithm?
    • And if you
      return Error("Another error", StatusCode::SUCCESS);

It is recommended that all errors are reported using the Warning() or Error() methods, due to the nice feature of printing statistics at the end of the job. It is also good practice that you always print a warning or error before returning StatusCode::FAILURE

Further reading

A more extensive introduction to job configuration using Python is available here and here

-- MarcoCattaneo - 27-Jan-2010

-- MarcoClemencic - 13-Sep-2011

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Topic revision: r6 - 2011-09-21 - MarcoCattaneo
 
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