Conveners
End User Perspective
- Enrico Guiraud (CERN, University of Oldenburg (DE))
End User Perspective
- Enrico Guiraud (CERN, University of Oldenburg (DE))
Widespread distributed processing of big datasets has been around for more than a decade now thanks to Hadoop, but only recently higher-level abstractions have been proposed for programmers to easily operate on those datasets, e.g. Spark. ROOT has joined that trend with its RDataFrame tool for declarative analysis, which currently supports local multi-threaded parallelisation. However,...
I would like to share my path of learning ROOT and acquiring software skills as a young physicist. I started learning ROOT in my 2nd year of physics bachelors with little of programming knowledge and some experience in C. I found mostly outdated docs and code from old guard physicists (overuse of pointers, new, delete, single file long macros, no OOP, …). What followed was 3 years of learning...
Most of the ATLAS analyses do their final step by processing TTree-based ntuples. As actual analysis selection optimisations take place at this step, it is crucial that one can process all events in a timely fashion. A (personal) experience writing a set of ROOT-based algorithms to process ntuples and create final histograms will be presented. More than 2 TB of data can be processed in about...
In 2016, development of an open source C++ library for multi-dimensional histograms in collaboration with the Boost community started, which leverages modern C++11 features such as variadic templates and template meta-programming (TMP). Variadic templates make code possible that works for arbitrary dimensions. TMP allows one to write histograms which compile to very efficient assembler while...
TRooFit is an extension of the RooFit toolkit, providing a set of classes that are inspired by core ROOT objects (specifically histograms and histogram stacks) but are fully-functional RooFit pdfs or functions. TRooFit's TRooH1D and TRooHStack are fillable and drawable in the same way as a TH1D and THStack, but are simultaneously concrete RooFit PDFs that can be fit to a RooFit dataset....
I have been using ROOT as an undergraduate and graduate student for about seven years now. The first scripts I ever wrote were ROOT macros. From naive histogram-filling in MakeClass.C to writing python wrapper-classes and analyzing unbinned fits, much of my development as a programmer has taken place in the context of ROOT.
In this talk, I present needs and examples of ROOT usage from fellow...
ROOT is a universal data analyzing library, which is not only used by particle physicists, but also by nuclear physicists. This presentation will focus on the data analysis of "small" datasets (10's GB) from a typical nuclear physics experiment, parallelization for beginners and a viable alternative to the current TTreeReader class. Missing features will also be addressed from a user perspective.
This talk reports on experiences and lessons learned moving from particle physics via software development to data science. It explains why we are still using ROOT from time to time and highlights some of its features making data analysis simple and fast. It also presents a few ideas to improve common tasks in ROOT and TMVA. Some annoyances and problems with ROOT are shown as well.
The aim of this talk is twofold: to summarize ROOT prompt options by simple use cases, and to introduce the newly introduced --strict flag. ROOT prompt, which runs C++ interpreter in its background, supports many features while not many of those are known to users. In this talk, we would like to summarize these options classified by simple use cases.
Second part is dedicated to an option...
