Proceedings of SciPy 2022

The generation of random variates is an important tool that is required in many applications. Various software programs or packages contain generators for standard distributions like the normal, exponential or Gamma, e.g., the programming language R and the packages SciPy and NumPy in Python.

Machine learning models are often represented by functions given by computer programs. Optimization of such functions is a challenging task because traditional derivative based optimization methods with guaranteed convergence properties cannot be used.

A common technique adopted by the Search For Extraterrestrial Intelligence (SETI) community is monitoring electromagnetic radiation for signs of extraterrestrial technosignatures using ground-based radio observatories.

Webots is a popular open-source package for 3D robotics simulations. It can also be used as a 3D interactive environment for other physics-based modeling, virtual reality, teaching or games. Webots has provided a simple API allowing Python programs to control robots and/or the simulated world, but this API is inefficient and does not provide many "pythonic" conveniences.

Space is more popular than ever, with the growing public awareness of interplanetary scientific missions, as well as the increasingly large number of satellite companies planning to deploy satellite constellations.

We present here the idea behind Papyri, a framework we are developing to provide a better documentation experience for the scientific ecosystem.

Though PINNs (physics-informed neural networks) are now deemed as a complement to traditional CFD (computational fluid dynamics) solvers rather than a replacement, their ability to solve the Navier-Stokes equations without given data is still of great interest.

Cilia are organelles found on the surface of some cells in the human body that sweep rhythmically to transport substances. Dysfunction of ciliary motion is often indicative of diseases known as ciliopathies, which disrupt the functionality of macroscopic structures within the lungs, kidneys and other organs.

Modern engineering models are complex, with dozens of inputs, uncertainties arising from simplifying assumptions, and dense output data. While major strides have been made in the computational scalability of complex models, relatively less attention has been paid to user-friendly, reusable tools to explore and make sense of these models.

Average-atom models are an important tool in studying matter under extreme conditions, such as those conditions experienced in planetary cores, brown and white dwarfs, and during inertial confinement fusion.

This paper introduces *monaco*, a Python library for conducting Monte Carlo simulations of computational models, and performing uncertainty analysis (UA) and sensitivity analysis (SA) on the results.

Rapid Application Development (RAD) is the ability to rapidly prototype an interactive interface through frequent feedback, so that it can be quickly deployed and delivered to stakeholders and customers.

Deep metric learning (DML) methods generally do not incorporate unlabelled data. We propose borrowing components of the variational autoencoder (VAE) methodology to extend DML methods to train on semi-supervised datasets.

Data driven advances dominate the applied sciences landscape, with quantum chemistry being no exception to the rule. Dataset biases and human error are key bottlenecks in the development of reproducible and generalized insights.

In recent years we are seeing exponential growth in the space sector, with new companies emerging in it. On top of that more people are becoming fascinated to participate in the aerospace revolution, which motivates students and hobbyists to build more High Powered and Sounding Rockets.

Meteorologists require information about the spatiotemporal distribution of winds in thunderstorms in order to analyze how physical and dynamical processes govern thunderstorm evolution. Knowledge of such processes is vital for predicting severe and hazardous weather events.

popmon is an open-source Python package to check the stability of a tabular dataset.

The Geoscience Community Analysis Toolkit (GeoCAT) team develops and maintains data analysis and visualization tools on structured and unstructured grids for the geosciences community in the Scientific Python Ecosystem (SPE).

Software data analytic workflows are a critical aspect of modern scientific research and play a crucial role in testing scientific hypotheses.

Human languages' semantics and structure constantly change over time through mediums such as culturally significant events. By viewing the semantic changes of words during notable events, contexts of existing and novel words can be predicted for similar, current events.

Due to the fact that the SARS-CoV-2 pandemic reaches its peak, researchers around the globe are combining efforts to investigate the genetics of different variants to better deal with its distribution. This paper discusses phylogeographic approaches to examine how patterns of divergence within SARS-CoV-2 coincide with geographic features, such as climatic features.

pyAudioProcessing is a Python based library for processing audio data, constructing and extracting numerical features from audio, building and testing machine learning models, and classifying data with existing pre-trained audio classification models or custom user-built models.

The ability to produce richly-attributed synthetic populations is key for understanding human dynamics, responding to emergencies, and preparing for future events, all while protecting individual privacy. The Likeness toolkit accomplishes these goals.

This paper walks through the ploomber interactive tutorial.

Scikit-HEP has grown rapidly over the last few years, not just to serve the needs of the High Energy Physics (HEP) community, but in many ways, the Python ecosystem at large. AwkwardArray, boost-histogram/hist, and iminuit are examples of libraries that are used beyond the original HEP focus. In this paper we will look at key packages in the ecosystem.

It is often much easier and less expensive to collect data than to label it. Active learning (AL) responds to this issue by selecting which unlabeled data are best to label next.

Codebraid Preview is a VS Code extension that provides a live preview of Pandoc Markdown documents with optional support for executing embedded code. Unlike typical Markdown previews, all Pandoc features are fully supported because Pandoc itself generates the preview.

All physical and astronomical imaging observations are degraded by the finite angular resolution of the camera and telescope systems. The recovery of the true image is limited by both how well the instrument characteristics are known and by the magnitude of measurement noise.

When it became clear in early 2020 that COVID-19 was going to be a major public health threat, politicians and public health officials turned to academic disease modelers like us for urgent guidance.

Statsmodels, a Python library for statistical and econometric analysis, has traditionally focused on frequentist inference, including in its models for time series data.

In the early 1990s the Automated Coastal Engineering Systems, ACES, was created with the goal of providing state-of-the-art computer-based tools to increase the accuracy, reliability, and cost-effectiveness of Corps coastal engineering endeavors.

For students across domains and disciplines, the message has been communicated loud and clear: data skills are an essential qualification for today’s job market.

Reliance on the normal curve as a tool for measurement is almost a given. It shapes our grading systems, our measures of intelligence, and importantly, it forms the mathematical backbone of many of our inferential statistical tests and algorithms.

Toxoplasma gondii is the parasitic protozoan that causes disseminated toxoplasmosis, a disease that is estimated to infect around one-third of the world's population. TSeg is developed for segmenting, tracking, and classifying the motility phenotypes of T. gondii in 3D microscopic images.

The use of several open source scientific packages in the Schrödinger Materials Science Suite will be discussed.

Galyleo is an open-source, extensible dashboarding solution integrated with JupyterLab.

Most semantic image annotation platforms suffer severe bottlenecks when handling large images, complex regions of interest, or numerous distinct foreground regions in a single image. We have developed the Semi-Supervised Semantic Annotator (S3A) to address each of these issues and facilitate rapid collection of ground truth pixel-level labeled data.

We report on progress in developing and extending the new (ASDF) format we have developed for the data from the James Webb and Nancy Grace Roman Space Telescopes since we reported on it at a previous Scipy.