CodeMeta overview

This page gives a succinct overview of all software pages that export to CodeMeta. Warning: this feature is still in development, so the generated CodeMeta data might still change.
2024_domain_adaptation_methods_lst_results
Results from the study presented in the article entilted _Comparative study of unsupervised domain adaptation techniques applied to gamma-ray astronomy with the CTAO Large Sized Telescope-1_
2025-stereograph
This repository contains pre-trained models, computed results, and analysis code for evaluating machine learning approaches (Random Forests, FCNs, and GNNs) on gamma-ray event reconstruction tasks.
agataselector
This selector is meant to analyze the data of AGATA+$Ancillary, producing various histograms and performing kinematic calculations and other operations useful for Doppler correction and other analysis tasks. The starting point of the selector are the ROOT files produced by femul. The code is a wo...
agnpy
agnpy is a python package focusing on the computation of the radiative processes of relativistic particles accelerated in the jets of Active Galactic Nuclei (AGN). It includes classes describing the galaxy components responsible for line and thermal emission and calculates the absorption due to g...
Aladin Lite
An astronomical HiPS visualizer in the browser.
ATLAS Open Data 13 TeV analysis C++ framework
A repository with 12 high energy physics analysis examples using the ATLAS Open Data 13 TeV dataset released in 2020. It is written in C++ and some bash scripts. * Documentation of the code: http://opendata.atlas.cern/release/2020/documentation/frameworks/cpp.html * Documentation of the analysis:...
cds-escape-tutorials
Jupyter Notebook tutorials using astronomical databases and Virtual Observatory tools
CTLearn: Deep learning for imaging atmospheric Cherenkov telescopes event reconstruction
CTLearn is a high-level Python package providing a backend for training deep learning models for the reconstruction of imaging atmospheric Cherenkov telescope events using TensorFlow.
Dark matter constraints from dwarf galaxies: a data-driven LAT analysis
Python code to derive data-driven upper limits on the thermally averaged, velocity-weighted pair-annihilation cross-section (velocity-independent) of a user-defined particle dark matter model using the expected differential gamma-ray spectrum of pair-annihilation events (provided by the user) as ...
Dockerfile to extract Gravitational Wave data from the ESCAPE datalake
This is a container to extract Gravitational Wave (GW) data from the datalake using Rucio and feed 1 second GW frames to the GW pipelines.
eossr
<p><img alt="eossr_logo" src="docs/images/eossr_logo_200x100.png" /></p><h1>The ESCAPE OSSR library</h1><p>The eOSSR is the Python library to programmatically manage the ESCAPE OSSR.In particular, it includes:</p><ul><li>an API to access the Zenodo and the OSSR, retrieve records and publish conte...
ESCAPE template project
An example of software project template for the ESCAPE 2020 European project
ESFRI Science Analysis Platform
ESAP is a science platform toolkit: an integrated set of software components which ESFRIs, ESCAPE project partners, and other groups can use to rapidly assemble and deploy platforms that are customized to the needs of their particular user communities and which integrate their existing service po...
FairMQ
C++ Message Queuing Library and Framework
GammaLearn
GammaLearn is a collaborative project to apply deep learning to the analysis of low-level Imaging Atmospheric Cherenkov Telescopes such as CTA. It provides a framework to easily train and apply models from a configuration file. Learn more at https://purl.org/gammalearn
Gammapy: Python toolbox for gamma-ray astronomy
Gammapy analyzes gamma-ray data and creates sky images, spectra and lightcurves, from event lists and instrument response information; it can also determine the position, morphology and spectra of gamma-ray sources. It is used to analyze data from H.E.S.S., Fermi-LAT, HAWC, and the Cherenkov Tele...
gLike
gLike is a general-purpose ROOT-based code framework for the numerical maximization of joint likelihood functions. The joint likelihood function has one free parameter (named g) and as many nuisance parameters as wanted, which will be profiled in the maximization process.
G-Tomo
The G-Tomo scientific data application (SDA) created by the EXPLORE project allows users to extract 1d profiles and 2d maps from the latest 3d dust extinction maps based on Gaia eDR3 and 2MASS data (Lallement et al. 2022).
HiPeRTA
HiPeRTA is a C++ library providing High Performance computing algorithms which provide full C++ programs from HiPeCTA C++ sources for the Cherenkov Telescope Array (CTA) low-level data analysis real time reconstruction. It takes advantage of the latest SIMD (Single input multiple data) operations...
IndexedConv
The indexed operations allow the user to perform convolution and pooling on non-Euclidian grids of data given that the neighbors pixels of each pixel is known and provided. It gives an alternative to masking or resampling the data in order to apply standard Euclidian convolution. This solution h...
Jupyter-CASA
A Jupyter kernel for CASA, a popular data processing suite for radio astronomy. The software is packaged together with CASA as a Docker container.
LOFAR software stack (ESCAPE 2020 edition)
LOFAR software stack for usage in the ESCAPE project. This is a Singularity image of a specific version of the LOFAR software stack.
MOC Lib Rust, MOCCLi, MOCWasm and MOCSet
Rust implementation of the IVOA MOC standard (MOC Lib Rust); associated command line tool (MOCCli) and Javascript/WebAssembly wrapper to manipulate MOCs in Web Browsers (MOCWasm).
MOCpy
Python library to easily create and manipulate MOCs (Multi-Order Coverage maps)
ossr-curation
Open curation for the ESCAPE OSSR using gitlab merge requests.
Pipeline for HCG-16 Project
This repository hosts a pipeline to reproduce the data reduction and analysis of Jones et al. 2019.
R3BRoot
Software for simulations and data analysis of Reactions with Relativistic Radioactive Beams (R3B) experiments at GSI/FAIR
SKAO Science Data Challenge 1 Solution Workflow
The SKA Science Data Challenge 1 (SDC1, https://astronomers.skatelescope.org/ska-science-data-challenge-1/) tasked participants with identifying and classifying sources in synthetic radio images. Here we present an environment and workflow for producing a solution to this challenge that can easil...
timewise-sup: The Timewise Subtraction Pipeline v0.5.1
The Timewise Subtraction Pipeline produces mid-infrared difference photometry based on measurements by the WISE satellite
ZenodoCI
The library is intended to be part of a complete CI pipeline. This stage deploys to Zenodo the files found in the ./build directory, configured in the .gitlab-ci.yml file