Curated list of interferometric software, methods and techniques
This list was developed during the 2024 Spatio-spectral Modeling for Interferometric Data Workshop (go.nrao.edu/ssmid)
Learning how to contribute and using git/github? See the list of resources at the bottom of this list!
- CASA
- casangi
- pyuvdata
- casa-formats-io
- vis_sample -- simulate an image `seen' by an interferometer based on a provided image and uv coverage
- CASA - includes several algorithms in tclean (Max. Entropy; Adaptive Scale Pixel)
- CASA Docker Container - Docker container for CASA 6.6.3 built within redhat/ubi8. This container also contains a miniconda python package manager with an 'astro_env' set up to use astropy, spectral-cube, reproject. Use commands: source ~/miniconda3/etc/profile.d/conda.sh' and 'conda activate astro_env' to activate.
- casangi
- MPoL
- MrBeam
- LibRA
- wsclean
- IMAGER
- GILDAS-MAPPING - documentation is out of date
- IRIS (Bayesian Imaging with Score-Based Priors)
- fitsconcat - Fast(er) cube creation via concatenation of individual image channels into a larger FITS cube
- radio-astro-tools -- spectral-cube, radio-beam, pvextractor, casa-formats-io
- bettermoments -- moment map making, including improved line center methods
- eddy -- rotation map fitting (protoplanetary disks)
- gofish --Stack line emission leveraging known structure of a system (protoplanetary disks)
- velocity_tools -calculation of Keplerian rotation velocity map -deprojection of relative coordinates for a given inclination and rotation angles and an arbitrary center -calculation of velocity gradient, assuming solid velocity rotation
- disksurf - Measure the molecular emission surface of protoplanetary disks
- FERIA - Flat Envelope model with Rotation and Infall under Angular momentum conservation
- keplerian_mask - Make a Keplerian mask for CLEANing with CASA.
- KeplerFit - A small piece of code to fit a Keplerian velocity distribution model to position-velocity data. *Developer is no longer working in astronomy
- GALARIO - uses GPUs to speed up the computation of the synthetic visibilities given a model image (or an axisymmetric brightness profile) and their comparison to the observations. *Developer is no longer working in astronomy
- discminer
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python packaging guide -- guide for making Python packages
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radio-astro-tools tutorials -- tutorials on using spectral-cube, fitting with spectral-cube, parallelization with dask, creating position-velocity diagrams, signal masking and moment map creation, cube reprojection
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Visread: Examining DSHARP AS 209 Weights and Exporting Visibilities -- uses CASA tools to examine the visibilities, visibility residuals, and weights of a real multi-configuration dataset from the DSHARP survey.
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auto_selfcal -- automated continuum self-calibration for ALMA and VLA data
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python packaging guide -- guide for making Python packages
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CHTC Guides on making Docker Containers -- guides on how to build/deploy Docker containers on your own computer and CHTC resources
- CARTA - Cube Analysis and Rendering Tool for Astronomy: a next-generation image visualization and analysis tool designed for ALMA, VLA, and SKA pathfinders.
- friendlyVRI -- simulate what a provided image will look like to in the `eyes' of an interferometer and its possible configurations
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Introduction to version control in Git for scientists -- a nice little blog post with the basics how-to for git. Explains basic git terms and how version control works - with visuals!
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Pull request workflow overview
- Make your own fork of this repository:
- Add new entries to the list, either on your own machine (make a local clone), or directly on github by pressing the pencil on the upper-right of the README file:
- Commit your new entries to your forked repository:
- Create a new pull request (PR) from your fork to the main branch:
- After the PR is merged into the main repository, update your forked repository before adding new entries. Use the "Sync fork" button here:
- Make your own fork of this repository: