Python helper wrappers for HEASoft UVOT analysis tools.
- Runs uvotdetect and generates region files for all observations
- Rudimentary data quality check by displaying all images in ds9
- Runs uvotsource on all observations
-- currently set up for producing observation-by-observation light curve data (if multiple exposures exist per observation, they are summed) and SED points
XPA , DS9, HEASoft (at least for Swift), CALDB(with data for at least for Swift)
Python packages:
$> pip -r install requirements.txt
To see all available options:
$> python run_uvot_analysis.py --help
$> python run_uvot_analysis.py -p /path/to/Swift/data --detect
The directory /path/to/Swift/data/ should contain UVOT data strucutres from all observations (typically directories titled e.g., 00034934001)
To run with a single observation:
$> python run_uvot_analysis.py -p /path/to/Swift/data -obs 00034934001 --detect
$> python run_uvot_analysis.py -p /path/to/Swift/data --check
To view images for a single observations, run:
$> python run_uvot_analysis.py -p /path/to/Swift/data -obs 00034934001 --check
The following will run uvotsource on all observations and store photometry data in photometry.fits (in fits format)
$> python run_uvot_analysis.py -p /path/to/Swift/data --measure
To only parse photometry data and store it in MySource_photometry.cvs (in csv format; same formats as supported by astropy.table).
NOTE: Do this if uvotsource has already been run with --measure
$> python run_uvot_analysis.py -p /path/to/Swift/data --measure -o MySource_phometry.csv --extract_only
As in previous steps, this works for a single observation as well.
$> python run_uvot_analysis.py -p /path/to/Swift/data --measure -obs 00034934001 -o MySource_photometry.fits