Related papers: colorspace: A Python Toolbox for Manipulating and …
We present CONAN (COde for exoplaNet ANalysis), an open-source Python package for comprehensive analyses of exoplanetary systems. It provides a unified Bayesian framework to simultaneously analyze diverse exoplanet datasets to derive global…
In these lecture notes, a selection of frequently required statistical tools will be introduced and illustrated. They allow to post-process data that stem from, e.g., large-scale numerical simulations (aka sequence of random experiments).…
We examine several currently used techniques for visualizing complex-valued functions applied to modular forms. We plot several examples and study the benefits and limitations of each technique. We then introduce a method of visualization…
\textsc{Pykat} is a Python package which extends the popular optical interferometer modelling software \textsc{Finesse}. It provides a more modern and efficient user interface for conducting complex numerical simulations, as well as…
Cosmic-ray observatories necessarily rely on Monte Carlo simulations for their design, calibration and analysis of their data. Detailed simulations are very demanding computationally. We present a python-based package called ShowerModel to…
Choropleth maps, which utilize color schemes to visualize spatial patterns and trends, are simple yet effective tools for geographic data analysis. As such, color scheme design is a critical aspect of choropleth map creation. The…
relentless is an open-source Python package that enables the optimization of objective functions computed using molecular dynamics simulations. It has a high-level, extensible interface for model parametrization; setting up, running, and…
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…
This paper is a guide to the installation and use of the Python package PYESSENCE. PYESSENCE is designed to evolve linear perturbations to Coupled Quintessence models with a arbitrary number of cold dark matter (CDM) fluids and dark energy…
Crystalline interfaces are of highly importance in many practical applications. To conduct effective simulation and analysis for coincident site lattice (CSL) interfaces, effective programmes are of high demand in building their CSL…
This is a companion Focus Demonstration article to the PyMUSE python package, demonstrating its usage and utilities for VLT/MUSE data analysis, that include a wide range of options for spectra extractions, the creation of different types of…
With the prevalence of image editing techniques, users can create fantastic synthetic images, but the image quality may be compromised by the color/illumination discrepancy between the manipulated region and background. Inharmonious region…
Scalable learning for planning research generally involves juggling between different programming languages for handling learning and planning modules effectively. Interpreted languages such as Python are commonly used for learning routines…
We are on the verge of a revolutionary era in space exploration, thanks to advancements in telescopes such as the James Webb Space Telescope (\textit{JWST}). High-resolution, high signal-to-noise spectra from exoplanet and brown dwarf…
The emergence of data-driven computational materials science offers unprecedented opportunities to explore complex material landscapes, complementing experimental research with the discovery of novel compounds. To enable these developments,…
PySymmPol is a Python package designed for efficient manipulation of symmetric polynomials. It provides functionalities for working with various types of symmetric polynomials, including elementary, homogeneous, monomial symmetric, (skew-)…
We present iSLAT (the Interactive Spectral-Line Analysis Tool), a python-based graphical tool that allows users to interactively explore and manually fit line emission observed in molecular spectra. iSLAT adopts a simple slab model that…
We present SliderSpace, a framework for automatically decomposing the visual capabilities of diffusion models into controllable and human-understandable directions. Unlike existing control methods that require a user to specify attributes…
In this paper, we investigate the effect of color space selection on detectability and discriminability of colored objects under various conditions. 20 color spaces from the literature are evaluated on a large dataset of simulated and real…
Explainability techniques for data-driven predictive models based on artificial intelligence and machine learning algorithms allow us to better understand the operation of such systems and help to hold them accountable. New transparency…