Using GANGA with AMAAthena

Introduction

This document gives an step-by-step instruction for running AMAAthena within GANGA on a NIKHEF desktop (e.g. ribble). AMAAthena is a Athena package providing ... developed at NIKHEF. GANGA is an official ATLAS grid utility for distributed data analysis.

The examples below assumes that:

Users have the following Athena job option files in the run directory of the AMAAthena package
AMAAthena_jobOptions.py
Trigger_jobOptions.py
Users have the following AMA driver configuration files in the run directory of the AMAAthena package
exampleaod.conf
reader.conf
Analysis is performed on an ATLAS dataset: fdr08_run2.0052280.physics_Muon.merge.AOD.o3_f8_m10

Preparation

1. follow the CMT instructions to setup your CMTHOME directory
2. checkout the AMAAthena package from CVS
3. make sure you will start GANGA with a clear environment without any Athena and CMT setup

Starting GANGA

Typing the following commands within the directory: PhysicsAnalysis/AnalysisCommon/AMA/AMAAthena/cmt

% source /project/atlas/nikhef/dq2/dq2_setup.sh.NIKHEF
% export DPNS_HOST=tbn18.nikhef.nl
% export LFC_HOST=lfc-atlas.grid.sara.nl
% source /project/atlas/nikhef/ganga/etc/setup.[c]sh
% ganga --config-path=/project/atlas/nikhef/ganga/config/Atlas.ini.nikhef

Magic functions for cmtsetup

Inside GANGA, one could deal with the complex CMT setup with two magic functions.

The following example shows how to setup the CMT environment for Athena 14.2.0 in 32 bit mode.

In [1]: config.Athena.CMTHOME = '/your/cmthome'
In [2]: cmtsetup 14.2.0,32
In [3]: setup

Running AMAAthena on Stoomboot

Using StagerDataset

Create a new job

In [1]: j = Job()

Setup the application:

In [2]: j.application = AMAAthena()
In [3]: j.application.option_files += [ File('../run/AMAAthena_jobOptions.py'), File('../run/Trigger_jobOptions.py') ]
In [4]: j.application.driver_config.config_file = File('../run/exampleaod.conf')
In [5]: j.application.driver_config.include_file += [ File('../run/reader.conf') ]
In [6]: j.application.max_events = '1000'
In [7]: j.application.prepare()

Setup the inputdata:

In [8]: j.inputdata = StagerDataset()
In [9]: j.inputdata.dataset += [ 'fdr08_run2*physics_Muon*AOD*o3*' ]

Setup the job splitter (optional):

In [10]: j.splitter = StagerJobSplitter()
In [11]: j.splitter.numfiles = 2

Setup the backend:

In [12]: j.backend = PBS()

Submit the job:

In [13]: j.submit()

Working in progress

1. supporting StagerDataset for jobs on the grid (LCG/NG)