PyHEP 2021 (virtual) Workshop

Session

Plenary Session Monday

5 Jul 2021, 14:00

Conveners

Plenary Session Monday

• Oksana Shadura (University of Nebraska Lincoln (US))
• Eduardo Rodrigues (University of Liverpool (GB))

Presentation materials

Youtube live feed - recorded

54. Welcome and workshop overview

Eduardo Rodrigues (University of Liverpool (GB))

05/07/2021, 14:00

53. Level-up your Python (Part I)

Henry Fredrick Schreiner (Princeton University)

05/07/2021, 14:10

Tutorial

This is a short course in intermediate Python. Attendees will learn about class design patterns, the python memory model, debugging, profiling, and more.

55. Astropy (cancelled)

Dr Brigitta Sipocz

05/07/2021, 15:10

18. A Python package for distributed ROOT RDataFrame analysis

Vincenzo Eduardo Padulano (Valencia Polytechnic University (ES))

05/07/2021, 15:40

Notebook talk

The declarative approach to data analysis provides high-level abstractions for users to operate on their datasets in a much more ergonomic fashion compared to previous imperative interfaces. ROOT offers such a tool with RDataFrame, which has been tested in production environments and used in real-world analyses with optimal results. Its programming model acts by creating a computation graph...

13. Monolens: view part of your screen in grayscale or simulated color vision deficiency

Dr Hans Peter Dembinski (TU Dortmund)

05/07/2021, 16:40

Lightning talk

Monolens is a platform-independent app written in Python that uses the Qt framework (PySide6) to create a window on the screen, which shows the part under the window in grayscale or simulated color vision deficiency. The purpose of this app is to make it easy to preview how scientific plots would appear in b/w print or to a person with color vision deficiency. While there are other ways to...

17. Easily report the progress of a program to your mobile

Matias Senger (Universitaet Zuerich (CH))

05/07/2021, 16:50

Lightning talk

Many times we perform automated tasks that demand a lot of time (hours, days, weeks), for example some measurement in the lab sweeping some parameter and acquiring data. Furthermore, no matter how much care we have when coding, there is always the possibility for some unexpected problem to occur and stop the execution of our program, without us noticing it (unless we go there and see it...

2. Create the shell experience thanks to cmd module

Olivier Mattelaer (UCLouvain)

05/07/2021, 17:00

Lightning talk

I will present the idea of the python module cmd which allows to have a shell with dedicated command, auto-completion, help.

In a second stage, I will present the customization that we have done within MG5aMC allowing to present a fully functional experience and various scenario under which this module is used.

4. Detector design for HL-LHC in FreeCAD using python scripts

Christophe Delaere (Universite Catholique de Louvain (UCL) (BE))

05/07/2021, 17:10

Notebook talk

The LHC machine is planning an upgrade program which will smoothly bring the luminosity to about $5-7.5\times10^{34}$cm$^{-2}$s$^{-1}$, to possibly reach an integrated luminosity of $3000-4000\;$fb$^{-1}$ over about a decade. This High Luminosity LHC scenario, HL-LHC, starting in 2027, will require an upgrade program of the LHC detectors known as Phase-2 upgrade. As part of the HL-LHC detector...

33. Computing tag-and-probe efficiencies with Apache Spark and Apache Parquet

Andre Frankenthal (Princeton University (US))

05/07/2021, 17:40

Notebook talk

In this talk we demonstrate a new framework developed by the muon physics object group in CMS to compute tag-and-probe (T&P) efficiencies and scale factors by leveraging the power and scalability of Apache Spark clusters. The package, named “spark_tnp”, allows physics analyzers and other users to quickly and seamlessly compute efficiencies for their own custom objects and identification...