Related papers: AstronomyCalc: A python toolkit for teaching Astro…
We present cosmo_learn, an open-source python-based software package designed to simulate cosmological data and perform data-driven inference using a range of modern statistical and machine learning techniques. Motivated by the growing…
The Python package teareduce has been developed to support teaching activities related to the reduction of astronomical data. Specifically, it serves as instructional material for students participating in practical classes on the…
This elementary review covers the basics of working with astronomical data, notably with images, spectra and higher-level (catalog) data. The basic concepts and tools are presented using both application software (DS9 and TOPCAT) and…
Current and upcoming cosmological experiments open a new era of precision cosmology, thus demanding accurate theoretical predictions for cosmological observables. Because of the complexity of the codes delivering such predictions, reaching…
We aim at facilitating the visualization of astrophysical data for several tasks, such as uncovering patterns, presenting results to the community, and facilitating the understanding of complex physical relationships to the public. We…
We developed a Python based framework for astronomical image processing and analysis. Astronomical image loading, normalizing, stacking, and filtering processes represent visible range images from grayscale. Besides, the blending process…
Astronomy and astrophysics are witnessing dramatic increases in data volume as detectors, telescopes and computers become ever more powerful. During the last decade, sky surveys across the electromagnetic spectrum have collected hundreds of…
The usage of the high-level scripting language Python has enabled new mechanisms for data interrogation, discovery and visualization of scientific data. We present yt, an open source, community-developed astrophysical analysis and…
The large amount of cosmological data already available (and in the near future) makes necessary the development of efficient numerical codes. Many software products have been implemented to perform cosmological analyses considering one or…
We present the first public version (v0.2) of the open-source and community-developed Python package, Astropy. This package provides core astronomy-related functionality to the community, including support for domain-specific file formats…
As wide-field surveys yield ever more precise measurements, cosmology has entered a phase of high precision requiring highly accurate and fast theoretical predictions. At the heart of most cosmological model predictions is a numerical…
Over the past few years, the role of visualization for scientific purpose has grown up enormously. Astronomy makes an extended use of visualization techniques to analyze data, and scientific visualization has became a fundamental part of…
With the application of advanced astronomical technologies, equipments and methods all over the world, astronomy covers from radio, infrared, visible light, ultraviolet, X-ray and gamma ray band, and enters into the era of full wavelength…
X-ray astronomy is an important tool in the astrophysicist's toolkit to investigate high-energy astrophysical phenomena. Theoretical numerical simulations of astrophysical sources are fully three-dimensional representations of physical…
In this article, we present Gammapy, an open-source Python package for the analysis of astronomical $\gamma$-ray data, and illustrate the functionalities of its first long-term-support release, version 1.0. Built on the modern Python…
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…
We present a scalable, cloud-based science platform solution designed to enable next-to-the-data analyses of terabyte-scale astronomical tabular datasets. The presented platform is built on Amazon Web Services (over Kubernetes and S3…
The rapid growth in scale and complexity of both computational and observational astrophysics over the past decade necessitates efficient and intuitive methods for examining and visualizing large datasets. Here, I present {\it AstroBlend},…
The use of Python is noticeably growing among the scientific community, and Astronomy is not an exception. The power of Python consists of being an extremely versatile high-level language, easy to program that combines both traditional…
pocoMC is a Python package for accelerated Bayesian inference in astronomy and cosmology. The code is designed to sample efficiently from posterior distributions with non-trivial geometry, including strong multimodality and non-linearity.…