GoodRunsList in AMA

Introduction

This page explains how to use the GoodRunsLists within AMAAthena. GoodRunsLists make it possible to select specific datasets AND lumiblocks satisfying detector and data quality constraints. A more general Atlas tutorial can be found here: GRL Tutorial.

Prepare

There are a few steps to make, in order to get it all working.

1: Get an XML file

First of all, you need an XML file with the datasets and lumiblocks you want to run over. To make one yourself, go to Atlas Run Query and enter a query containing all DQ flags you need/like. This page has lots of examples and help functions to assist in forming a query.

Press Show Runs, wait for it... and inspect the results. On the bottom of the page you can choose to view in 'pretty mode', 'python dictionary', 'Root tree', but we need to dump it as an XML file. Choose this one. Now you have your XML file, check if it looks ok. (Obviously, it is also possible to take the XML file supplied by your group, Atlas or anyone else you assume knows it all.)

2: Edit the AMAAthena jo

The idea is now, to let AMAAthena only run over events that are in the selected lumiblocks and datasets, and skip the remainder. This is especially nice when you are running over millions of events. Make sure you have an updated version of AMA, by doing for exmaple 'svn update'. Compile if necessary, but check explicitly that in AMAAthena/share there is a file called AMAAthena_jobOptions_new_GRL.py.

Open this file and edit two things:

• the name of the XML file in ...
• the name without .xml but in ...

Run locally...

 AMAAthenaDriver data 100 ConfigFile=data.conf TRIG,DATA,GRL

(GRL calls the joboptions you just edited.) If you dump an ntuple, you can see from

 root> tree->Draw("lumiBlock")