On this page you will find a selection of software tools for analysis of primarily ALMA but also other interferometric data. Most tools (unless otherwise indicated) are developed for use with CASA but are in many cases general and adaptable to other packages.
Any questions should be directed to us and not the CASA help desk!!
When using any of these open source tools for your work, please remember to cite the relevant publications listed with the tools. An acknowledgement to the Nordic ALMA regional center would also be appreciated.
Please contact us with any request regarding the packages below, either to email@example.com .
This task is to compute synthetic visibilities from a single-dish (i.e. total-power) image (or image cube). A combined deconvolution of these visibilities with interferometric observations is the optimum approach for the image reconstruction of extended structures.
You can download the task SD2vis here.
STACKER is a library for stacking sources in interferometric data, i.e., averaging emission from different sources. The library allows stacking to be done directly on visibility data as well as in the image domain.
Stacking directly on the visibilities provides several advantages to stacking in the image domain. In particular the full uv data is available post-stacking allowing further analysis such as model fitting, and flagging problematic baselines were not obvious prior to stacking. Stacking on the visibilities has also been found to yield 20% higher SNR for simulated VLA data.
Further details on the code and the simulations can be found in Lindroos et al. (2015, MNRAS 446, 3502).
A tar file with the code, documentation, and installation instructions can be downloaded from here.
(The code currently supports Linux, and Mac support is being worked on).
Line-Stacker is an extension of Stacker, allowing stacking of spectral lines and not solely continuum. The release consists of a Python module. Most of the code is to be run within the CASA shell, except for a one dimensional version of the algorithm, supporting native Python2.7. Line-Stacker currently only supports Image stacking.
Some additional tools, allowing further analysis of the stack product are also included in the module.
Further details on the performances and capabilities of Line-Stacker will be found in Jolly et al. 2019 (to be submitted).
UVMULTIFIT is a versatile library for fitting models directly to visibility data, currently implemented in CASA. These models can depend on frequency and fitting parameters in an arbitrary algebraic way. We have tested the software with both synthetic data and real observations. In some cases (e.g., sources with sizes smaller than the diffraction limit of the interferometer), the results from the fit to the visibilities are far superior to the output obtained from a mere analysis of the deconvolved images. We give some illustrative examples in the software documentation and in Marti-Vidal et al. (2014) (A&A 563, 136, arXiv:1401.4984).
A tar file with the code, documentation, and installation instructions can be downloaded from here. We support the latter, which is compatible with the latest CASA versions. For other versions of UVMULTIFIT, please refer to this link and corresponding online documentation.
FAKEOBS is a CASA task to generate model visibilities from already-existing measurement sets. Let us suppose that there is a measurement with either real or simulated data. In this dataset, there are several sources observed (e.g., bandpass calibrator, flux/phase calibrator, and target). In addition, the target source may have been observed in mosaic mode. If we want to substitute all the visibilities of the target with simulations computed from any model image, this is the task to use.
This task can be downloaded from here.
This task is intended to be especially helpful for (early) checks of data quality, even before beginning with any calibration. Closure quantities (either phase or amplitudes closures) are independent of antenna gains, so any problem inherent to the data (i.e., independent of the calibration) should appear crystal-clear in the closure plots, especially those regarding the strongest sources (i.e., flux and/or bandpass calibrators).
This task can generate such plots and/or save the closure data in an external ascii file, so the user can later check and plot the closures by him/herself. The task also sorts the antennas from best to worse, in terms of the statistics of the closures where each antenna is involved.
This task can be downloaded from here.
Aperture Synthesis Simulator for Radio Astronomy. Based on python/matplotlib, it is fully interactive and the plots are updated almost in real time. Antennas can be dragged with the mouse. Number of antennas, observing frequency, observatory-source coordinates, visibility weighting, etc. can be changed on the fly. Generic images can be used as observed sources. An ideal program to teach Aperture Synthesis in Radio Astronomy.
The program can be downloaded from Launchpad.
Simple task to compute radial profiles of images (and image cubes). It generates plots and ascii files with the profile values.
Download this task from here.
This is the CASA task used for the conversion of ALMA-VLBI visibilities, from linear-circular (i.e., "mixed") polarization basis into circular-circular basis. The algorithm is described in Marti-Vidal et al. (2016)
CASA interactive task for a quick check of image residuals, but in Fourier space. It overplots the UV tracks of the baselines corresponding to selected antennas, so it should be easy to locate the antennas (and/or baselines) responsible of dynamic-range limitations.
The code (version 1.0-r2) can be downloaded from here.
A basic CASA simulator of ALMA full-polarization observations. Support for spectral-line simulations.
The code (version 1.2) can be downloaded from here (this requires less RAM than version 1.0; circular feeds are also implemented)
User-acknowledgements to the Nordic ARC
Users who receive support from the Nordic ARC node are required to put following acknowledgement in their publications:
AUTHOR NAME acknowledges support from the Nordic ALMA Regional Centre (ARC) node based at Onsala Space Observatory. The Nordic ARC node is funded through Swedish Research Council grant No 2017-00648.