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Current research provides methods to communicate uncertainty and adapts classical algorithms of the visualization pipeline to take the uncertainty into account. Various existing visualization frameworks include methods to present uncertain…
Bayesian Networks (BNs) are used in various fields for modeling, prediction, and decision making. pgmpy is a python package that provides a collection of algorithms and tools to work with BNs and related models. It implements algorithms for…
The current landscape of scientific research is widely based on modeling and simulation, typically with complexity in the simulation's flow of execution and parameterization properties. Execution flows are not necessarily straightforward…
Any optimization algorithm programming interface can be seen as a black-box function with additional free parameters. In this spirit, simulated annealing (SA) can be implemented in pseudo-code within the dimensions of a single slide with…
We present astroplan - an open source, open development, Astropy affiliated package for ground-based observation planning and scheduling in Python. astroplan is designed to provide efficient access to common observational quantities such as…
Microscopy, in particular scanning probe and electron microscopy, has been pivotal in improving our understanding of structure-function relationships at the nanoscale and is by now ubiquitous in most research characterization labs and…
Usability evaluation has received considerable attention from both the research and practice communities. While there are many evaluation tools available, the Software Usability Scale (SUS) is the most widely used. In this paper, we…
Scipp is heavily inspired by the Python library xarray. It enriches raw NumPy-like multi-dimensional arrays of data by adding named dimensions and associated coordinates. Multiple arrays are combined into datasets. On top of this, scipp…
Since Lorenz's seminal work on a simplified weather model, the numerical analysis of nonlinear dynamical systems has become one of the main subjects of research in physics. Despite of that, there remains a need for accessible, efficient,…
Abdominal aortic aneurysms (AAAs) are localized dilatations of the abdominal aorta that can lead to life-threatening rupture if left untreated. AAAs primarily affect older individuals, with high mortality rates following rupture, so early…
Gammapy is a Python package for high-level gamma-ray data analysis built on Numpy, Scipy and Astropy. It enables us to analyze gamma-ray data and to create sky images, spectra and lightcurves, from event lists and instrument response…
Since its start in 2014, the lightweight open source Python library Gammapy has come a long way to become a popular data analysis package for high-energy astrophysics. Selected as the official CTAO Science Analysis tool, it is also an…
Data exploration is an important step of every data science and machine learning project, including those involving textual data. We provide a novel language tool, in the form of a publicly available Python library for extracting patterns…
There are numerous approaches to building analysis applications across the high-energy physics community. Among them are Python-based, or at least Python-driven, analysis workflows. We aim to ease the adoption of a Python-based analysis…
ESASky is a science-driven discovery portal to explore the multi-wavelength sky and visualise and access multiple astronomical archive holdings. The tool is a web application that requires no prior knowledge of any of the missions involved…
Python for Power System Analysis (PyPSA) is a free software toolbox for simulating and optimising modern electrical power systems over multiple periods. PyPSA includes models for conventional generators with unit commitment, variable…
Fanpy is a free and open-source Python library for developing and testing multideterminant wavefunctions and related ab initio methods in electronic structure theory. The main use of Fanpy is to quickly prototype new methods by making it…
Access to astronomical data through archives and VO is essential but does not solve all problems. Availability of appropriate software for analyzing the data is often equally important for the efficiency with which a researcher can publish…
Instance Space Analysis is a methodology to evaluate algorithm performance across diverse problem fields. Through visualisation and exploratory data analysis techniques, Instance Space Analysis offers objective, data-driven insights into…
The astronomy, astroparticle and particle physics communities are brought together through the ESCAPE (European Science Cluster of Astronomy and Particle Physics ESFRI research infrastructures) project to create a cluster focused on common…