Now that SciPy 2020 is over, I would like to share the process I used to create the talk video. The effect was designed to recreate the feeling of watching an actual in-person talk. I will first cover parts, detailing what I got and some general suggestions, then I’ll discuss the filming process, and finally, I will cover the post-process procedure and software. The entire process took about a day and a half, with an overnight render, and cost about $200 (best compared to the cost of registration of a live conference).
Posted on December 13, 2019
(Last modified on March 20, 2020)
| Henry Schreiner
The foundational histogramming package for Python, boost-histogram, hit
beta status with version 0.6! This is a major update to the new
Boost.Histogram bindings. Since I have not written about boost-histogram
yet here, I will introduce the library in its current state. Version 0.6.2 was
based on the recently released Boost C++ Libraries1.72
Histogram package. Feel free to visit the docs, or keep
reading this post.
This Python library is part of a larger picture in the Scikit-HEP ecosystem
of tools for Particle Physics and is funded by DIANA/HEP and IRIS-HEP.
It is the core library for making and manipulating histograms. Other packages
are under development to provide a complete set of tools to work with and
visualize histograms. The Aghast package is designed to convert between
popular histogram formats, and the Hist package will be designed to make common
analysis tasks simple, like plotting via tools such as the mplhep package.
Hist and Aghast will be initially driven by HEP (High Energy Physics and
Particle Physics) needs, but outside issues and contributions are welcome and
encouraged.