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PyNOT : crr
This task takes an image (corrected or not) and performs a cosmic ray rejection by using a Laplacian kernel detection algorithm (van Dokkum 2001) implemented in Python as the package astroscrappy. The output of the task is a corrected image with an additional mask extension indicating which pixels have been flagged (0 if good or 1 if flagged as a cosmic ray hit).
The resulting FITS file can be inspected using the astropy command line function fitsinfo
.
An example of the output from pynot crr
would look something like this:
%] pynot crr raw_image.fits -o cosmic_ray_corrected_image.fits > crr_processing.log
%] fitsinfo cosmic_ray_corrected_image.fits
Filename: cosmic_ray_corrected_image.fits
No. Name Ver Type Cards Dimensions Format
0 DATA 1 PrimaryHDU 493 (1024, 1024) float64
1 ERR 1 ImageHDU 495 (1024, 1024) float64
2 MASK 1 ImageHDU 20 (1024, 1024) int64
Example Syntax
pynot crr -o OUTPUT input
Full example of command line syntax:
pynot crr [-h] -o OUTPUT [-n NITER] [--gain GAIN] [--readnoise READNOISE] [--sigclip SIGCLIP] [--sigfrac SIGFRAC] [--objlim OBJLIM] [--cleantype CLEANTYPE] input
Overview of parameters
- input
- Input filename
- --output (-o)
- Output filename of cleaned image [REQUIRED]
- --niter (-n): 2
- Number of iterations
- --gain: None
- Detector gain, e-/ADU. Read from the header by default
- --readnoise: None
- Detector read-out noise, e-. Read from the header by default
- --sigclip: 4.5
- Laplacian-to-noise limit for cosmic ray detection. Lower values will flag more pixels as cosmics
- --sigfrac: 0.3
- Fractional detection limit for neighboring pixels
- --objlim: 5.0
- Minimum contrast. Increase this value if cores of bright stars/skylines are flagged as cosmics
- --cleantype: 'meanmask'
- Cleaning filter (5x5): {'median', 'medmask', 'meanmask', 'idw'}, see astroscrappy for details