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Ethnomethodological fieldwork has long been acknowledged as a potentially valuable way of informing the design of technology. However, there is relatively little methodological support for this activity, particularly in relation to the…
In recent years, numerical simulations have become indispensable for addressing complex astrophysical problems. The MagnetoHydroDynamics (MHD) framework represents a key tool for investigating the dynamical evolution of astrophysical…
The Sand Atlas is a publicly accessible repository dedicated to the collection, processing, and sharing of high-resolution 3D models of sand-sized particles. This dataset offers valuable insights into the morphology of a wide variety of…
The Solar MAgnetic Connection HAUS tool (Solar-MACH) is an open-source tool completely written in Python that derives and visualizes the spatial configuration and solar magnetic connection of different observers (i.e., spacecraft or…
Nowadays interactive digital scientific environments have become an integral part of scientific computing in solving various scientific tasks in research, but also STEM education. We introduce SageMath or shortly Sage -- a free open…
DADApy is a python software package for analysing and characterising high-dimensional data manifolds. It provides methods for estimating the intrinsic dimension and the probability density, for performing density-based clustering and for…
Machine learning is an important part of the data science field. In petrophysics, machine learning algorithms and applications have been widely approached. In this context, Vietnam Petroleum Institute (VPI) has researched and deployed…
Loss landscapes are a powerful tool for understanding neural network optimization and generalization, yet traditional low-dimensional analyses often miss complex topological features. We present Landscaper, an open-source Python package for…
Spectropolarimetry, the observation of polarization and intensity as a function of wavelength, is a powerful tool in stellar astrophysics. It is particularly useful for characterizing stars and circumstellar material, and for tracing the…
Market area models, such as the Huff model and its extensions, are widely used to estimate regional market shares and customer flows of retail and service locations. Another, now very common, area of application is the analysis of catchment…
Pandas is defined as a software library which is used for data analysis in Python programming language. As pandas is a fast, easy and open source data analysis tool, it is rapidly used in different software engineering projects like…
Remotely sensed geospatial data are critical for applications including precision agriculture, urban planning, disaster monitoring and response, and climate change research, among others. Deep learning methods are particularly promising for…
Molecular dynamics (MD) simulations play a crucial role in resolving the underlying conformational dynamics of molecular systems. However, their capability to correctly reproduce and predict dynamics in agreement with experiments is limited…
Computational analysis has become ubiquitous within the heliophysics community. However, community standards for peer-review of codes and analysis have lagged behind these developments. This absence has contributed to the reproducibility…
In the context of proxy modeling for process systems, traditional data-driven deep learning approaches frequently encounter significant challenges, such as substantial training costs induced by large amounts of data, and limited…
An easy way to define and visualize geometry for PHITS input files introduced. Suggested FitsGeo Python package helps to define surfaces as Python objects and manipulate them conveniently. VPython assists to view defined geometry…
In a first course to classical mechanics elementary physical processes like elastic two-body collisions, the mass-spring model, or the gravitational two-body problem are discussed in detail. The continuation to many-body systems, however,…
Motivation: Peptides have attracted the attention in this century due to their remarkable therapeutic properties. Computational tools are being developed to take advantage of existing information, encapsulating knowledge and making it…
Python has become the prime language for application development in the Data Science and Machine Learning domains. However, data scientists are not necessarily experienced programmers. While Python lets them quickly implement their…
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…