The ALMA-VO Data Repository service offers ALMA data access through IVOA standard web-services/VO-apps or through a web-page. Currently we support single FITS files search [SCS, SIA and TAP] and complete data products (TAR files) [SCS and TAP]. The ALMA raw data (ASDMs) will be published soon.
The Jupyter OVerride for Astronomical Libraries (JOVIAL) is notebook-based cloud environment to process astronomical data on-line. This service provides Jupyter Notebooks to astronomers, that are executed in the cloud under a python environment. No installation required so is accesible from any device. This service is in beta testing so you need an account to use it. If you are interested in participating of this project please contact maray@inf.utfsm.cl
Documentation can be found in GitHub
The Advanced Computing for Astronomy Library (ACALib) is a package with state of the art Algorithms for Astronomers including novel algorithms produced by ChiVO and some HPC versions of them
The oficial documentation can be found in readthedocs
The source is publicly managed by the github service.
The Starlink's CUPID Python Wrapper. CUPID is part of the Starlink Software Collection <http://www.starlink.ac.uk/>, it provides a set of commands that identify and analyse clumps of emission within 1-, 2- and 3-dimensional data arrays. This stand-alone module aims to serve as an interface between CUPID implementation (C and Fortran) and Python. As such, users can simply import the module and use CUPID functions as if they were implemented in Python.
The official documentation can be found in readthedocs
We maintain this wrapper over the github service.
Python library to stack images of galaxies and other astronomical objects.
The official documentation can be found in readthedocs
The source is publicly managed by the github service.
This python package provides an easy interface and I/O operations for using astronomical libraries over Jupyter notebooks (and in general over Python ecosystems).
The source is publicly managed by the github service.
Astronomical Synthetic Data Observatory (ASYDO), a virtual service that generates synthetic spectroscopic data in the form of data cubes. The objective of the tool is not to produce accurate astrophysical simulations, but to generate a large number of labeled synthetic data, to assess advanced computing algorithms for astronomy and to develop novel Big Data algorithms.
This project includes all the code used by our (public) Data Access Layer (DAL), which even though is specific for our data-center layout, might help as a reference to other centers.
We maintain this development public under GitHub.
The objective of this project is to identify spectroscopical lines from ALMA-like cubes of spectral data using Machine Learning.
This code is publicly managed by GitHub.
Prototype to detect long-term variable starts from series of data points.
Prototype that uses asociation rules over identified spectra lines to find and associate new lines.
The code is maintained in GitHub
This code is our internal system for the automatic creation of accounts for all the authenticated services. This is specific for our layout and deployment, but it is a common problem in astronomical data centers.
For security issues, you need authentication to access to our repository
This prototype performs a Hierarchical Decomposition of Sources to be used in molecular clouds.
The code is managed at a GitHub