The master branch is currently v1.3-beta. rss_ringoccs is unable to run on the latest releases of Python (3.8 or 3.9) and it is recommended that 3.6 is used. There is active work in rewriting the project C89/C90 compliant code to allow for future use and ease of backwards and forward compatibility.
rss_ringoccs is a suite of open-source C and Python-based analysis tools for Cassini Radio Science (RSS) ring occultations. It was developed by Team Cassini at Wellesley College (Sophia Flury, Jolene Fong, Ryan Maguire, and Glenn Steranka) under the direction of Richard French, Cassini RSS Team Leader, with funding provided by the NASA/JPL Cassini project.
Version 1.2 was offically released on July 1, 2019.
Version 1.2.1 was a development version that incorporated changes between Versions 1.2 and 1.3.
Version 1.3-beta was officially released on January 12, 2021
The Cassini Radio Science Subsystem (RSS) was used during the Cassini orbital tour of Saturn to observe a superb series of ring occultations that resulted in high-resolution, high-SNR radial profiles of Saturn's rings at three radio wavelengths: 13 cm (S band), 3.6 cm (X band), and 0.9 cm (Ka band). Radial optical depth profiles of the rings at 1- and 10-km resolution produced by the Cassini RSS team, using state of the art signal processing techniques to remove diffraction effects, are available on NASA's Planetary Data System (PDS). These archived products are likely to be quite adequate for many ring scientists, but for those who wish to generate their own diffraction-reconstructed ring profiles from Cassini RSS observations, we offer rss_ringoccs: a suite of Python-based analysis tools for Cassini Radio Science (RSS) ring occultations.
The purpose of rss_ringoccs is to enable scientists to produce "on demand" radial optical depth profiles of Saturn's rings from the raw RSS data, without requiring a deep familiarity with the complex processing steps involved in calibrating the data and correcting for the effects of diffraction. The code and algorithms are extensively documented, providing a starting point for users who wish to test, refine, or optimize the straightforward methods we have employed. Our emphasis has been on clarity, sometimes at the expense of programming efficiency and execution time. rss_ringoccs does an excellent job of reproducing existing 1 km-resolution RSS processed ring occultation data already present on NASA's PDS Ring-Moons Node, but we make no claim to having achieved the state-of-the-art in every respect. We encourage users to augment our algorithms and to report on those improvements, so that they can be incorporated in future editions of rss_ringoccs.
Detailed installation instructions and full documentation are contained the
rss_ringoccs User Guide at https://github.com/NASA-Planetary-Science/rss_ringoccs/tree/master/docs/rss_ringoccs_User_Guide_V1.3.pdf.
For experienced users, we provide a rss_ringoccs Quick Start guide located at
https://github.com/NASA-Planetary-Science/rss_ringoccs/tree/master/docs/rss_ringoccs_Quick_Start_V1.3.pdf
Release notes are contained in https://github.com/NASA-Planetary-Science/rss_ringoccs/blob/master/ReleaseNotes.md
Source code documentation is found at https://rss-ringoccs.readthedocs.io/en/master/
Once rss_ringoccs has been installed and the necessary data and
ephemeris/geometry files have been downloaded to local storage, as describd in
the rss_ringoccs User Guide, users should first test rss_ringoccs using the
documented example scripts. Once all is well, users will be able to process a
set of Cassini RSS ring observations in batch mode. To simplify and expedite the
use of rss_ringoccs, we provide a Python script that performs the end-to-end
pipeline for a list of files contained in a reference ASCII text file. The
default list is the 1 kHz Cassini RSR files prior to the USO failure, which can
be found in the ./tables/ directory. This batch script implementation of the
pipeline is located in the ./pipeline/ directory. We suggest running the batch
script using the yes command as shown here:
yes | python e2e_batch.py
The rss_ringoccs User Guide includes several additional examples of end-to-end
processing scripts, as well as instructions to enable users to construct their
own batch end-to-end scripts.
If you have trouble with installation or execution of the rss_ringoccs package, we encourage you to post a issue to https://github.com/NASA-Planetary-Science/rss_ringoccs/issues. We will attempt to respond promptly, and ther users will benefit. Alternatively, you can write email directly to Richard French: rfrench_at_wellesley.edu.
If you use rss_ringoccs as the basis of a publication, please consider citing rss_ringoccs using the DOI:10.5281/zenodo.2548947
This work was supported by the NASA/JPL Cassini mission. We are especially grateful to Linda Spilker and Kathryn Weld for their encouragement and support, and to RSS Team Member Essam Marouf for developing the diffraction reconstruction technique that underlies this work.