This is an Analysis Framework that is composed of a set of python macros with the objective to manage the reading and analysis of the samples of the 2016 open data release.
The Framework is divided into two main functionalities, with examples:
In the first part, a set of seven analysis examples, (W, Z, H and beyond SM analysis) has been included.
Those analysis are macros in python with defined cuts that produce a set of histograms.
The code is fully customisable by the user, like: samples to use, histograms to produce, the cuts to apply.
The second part of the framework, always in python, is responsable to take those histograms and produce plots in a final publication-style, with the correct normalisations, colours, legends and style in general.
The code is fully customisable too, leaving the opportunity to the user to select the samples to use, histograms to produce, style to apply.
How can you use this?
More documentation is available at ATLAS GitHub repository:
Please note that the file you are going to download (atlas-outreach-data-tools-framework-1.1.tar.gz) is 26914 bytes big. On an average ADSL connection, it may take long to download it (about less than a minute at 1Mbps).
Moreover, if you use one of the provided Virtual Machines to perform your analyses, then you don't need to download datasets manually, because the VM will fetch all the necessary file chunks via the XRootD protocol.
Manual download of files via HTTP is only necessary if you would prefer not to use the XRootD protocol for one reason or another.