- Pipeline User Manuals and Data Handbooks
- Data Analysis FAQs
- Data Analysis Cookbooks
- Analysis Tools
- Quality Assurance and Known Issues
- Additional Resources
Pipeline User Manuals and Data Handbooks
The pipeline User Manuals and Guest Observer (GO) Data Handbooks describe data products, processing steps, calibration procedures, and known issues.
Data Analysis FAQs
Frequently Asked Questions (FAQs) for each instrument can be found on our Data Analysis FAQ page. These cover information about the data not necessarily in the instrument or proposal documentation, but that may be relevant for interpreting your results. All of the FAQs can be found here: Data Analysis FAQs.
Data Analysis Cookbooks
These documents provide simple "recipes" (i.e., descriptions and guided examples) for common data analysis objectives using SOFIA processed data. They are generally written for a graduate student audience and are intended to be used with the Data Handbooks (see above).
IRSA Data Retrieval
SOFIA data retrieval using the NASA/IPAC Infrared Science Archive.
I. Aperture Photometry (basic)
Aperture photometry on flux-calibrated FORCAST images (FITS files) using python and astropy.
II. Aperture Photometry (detailed)
A more detail explanation of the steps involved with aperture photometry using FORCAST data.
III. Periodic Noise Handling
How to clean up ringing background noise in FORCAST with a data file.
FORCAST Grism Spectra Series
I. Basic Inspection and Assessment
Python tutorial on plotting and analyzing data.
II. Basic Line Analysis
Includes minor "cleaning" of the LEVEL_3 data and then some basic emission line analysis including continuum fitting and subtraction, line flux measurement, and simple line fitting.
III. Custom Spectral Extraction
Utilizes Level 2 two-dimensional images to plot the aperture and do a simple custom extraction using a different aperture.
Data Recipe with 30 Doradus Publicly Available SDDT Data
Associated white paper: SOFIA Community Science I—HAWC+ Polarimetry of 30 Doradus
Guides users through Python analysis techniques using the 30 Doradus dataset, teaching readers how to probe HAWC+ data cubes and learn basic analysis techniques—such as plotting Stokes parameters, error maps, and polarization vectors—to jump-start their own research.
I. Data inspection with python
Python tutorial on plotting and analyzing grism data.
II. Telluric Correction with python
Retrieving and plotting atmospheric models from the the Planetary Spectrum Generator (PSG), manipulating and tuning models, subtracting them from grism data.
III. Velocity Shift
Python code for estimating the velocity shift of spectral lines as a result of the motion of Earth and a target.
I. How to View GREAT Spectra Using CLASS Utility
Finding a sample data set through modifying the baseline fit, averaging, and saving the result in a Flexible Image Transport System (FITS) file using the Continuum and Line Analysis Single-dish Software (CLASS) utility, the standard for single-dish heterodyne spectroscopy data reduction.
II. Data Inspection with Python
Inspection of the data structure and header information. Plotting spectra, visualizing image slices, producing moment maps, and extracting spectra.
III. Re-project data to GREAT resolution
Re-project other astronomical data to the pixel map of GREAT data for better comparison of the data.
IV. Data Visualization (python/JDAVIZ)
Visualizing datacubes in 2D and 3D using the python/jdaviz tool Cubeviz and glue.
V. Data Visualization (CARTA)
Visualizing datacubes along the X, Y, and Z dimensions using CARTA.
Basic Cube Analysis using SOSPEX
Basic spectroscopic cube analysis using the SOFIA python tool SPectrum Explorer (SOSPEX), which displays FIFI-LS and GREAT spectral cubes and allows the user to perform a number of basic analysis routines on them. The cube is shown as a 2D image (spatial image obtained as average along the wavelength dimension) and as a spectrum (sum of spatial pixels of the original cube).
SOFIA SPectral EXplorer (SOSPEX)
The SOSPEX tool, written by Dario Fadda and Ed Chambers, allows users to explore the final data cubes produced by the data reduction pipeline. An overview of its use can be found on the SOSPEX poster from the AAS.
The FLUXER IDL tool, written by Christof Iserlohe, allows users to fit the continuum and estimate line strengths in the final FIFI-LS data cubes.
Quality Assurance and Known Issues
Summary of QA Process and Keywords
Calibrated FORCAST imaging data processed before Cycle 3 (2015) do not include the on-source integration time listed in their headers. The document FORCAST Imaging Exposure Time outlines the procedure for calculating the on-source integration time in Level 2 and 3 merged and co-added data files for these observations.
Catalog of Known Issues for each Observing Series.
Infrared Data Analysis Techniques with Python (JWST example notebooks).
Data Analysis Talks
SOFIA School February 2022 meeting The SOFIA School aims to teach new SOFIA users how to reduce their data.
SOFIA User Code
GREAT data reduction Off position data reduction for the Orion B map using CLASS by Juan Luis Verbena. See also his talk about this code.
Inspect Sky Hot script - An annotated CLASS-script to check for emission in the reference position for a GREAT observations with an example.
HAWC+ data reduction SALSA Legacy Program data analysis code.
PhotoDissociation Region Toolbox
PDR Toolbox An open source tool for determining the physical parameters of photodissociation regions from observations. With spectral lines or continuum intensities, the PDR Toolbox can compute best-fit FUV incident intensity and cloud density based on our models of PDR emission. One can also fit H2 rovibrational emission excitation diagrams to determine temperature, column density, and ortho-to-para ratio.