EXAMPLES · TIME_REQUIREMENTS · BUGS · REFERENCES · SEE_ALSO
pet2spc -- bin contents of a Pixel Extraction Table into 1D spectra
pet2spc grism config
- Name of grism/prism image.
- Filename of grism/prism extraction configuration file.
- (usr_bpet = yes) [yes|no]
- Whether to use a background PET file.
- (weights = no) [yes|no]
- Compute and use optimal weights in 1D extraction.
- (do_flux = yes) [boolean]
- Whether to perform flux calibration.
- (out_spc = "") [string]
- Name to use for the output SPC file instead of the default.
- (drzpath = false) [boolean]
- Use the directory indicated by the system variable $AXE_DRIZZLE_PATH to located the input PET and write out the output spectra (SPC).
- (in_af = "") [string]
- Name to use for the input Aperture file instead of the default.
- (opet = "") [string]
- Name to use for the input object pixel extraction table file instead of the default.
- (bpet = "") [string]
- Name to use for the input background pixel extraction table file instead of the default.
- (out_spc = "") [string]
- Name to use for the output file with the spectra (instead of the default).
This task is used to transform the content of an Object Pixel Extraction Table (PET) into a set of 1D binned spectra in a Extracted Spectra File (SPC). The binning process is explained in more detail in the aXe manual.
In case that the object PET was created from a grism image with substantial sky background, "use_bpet=yes" extracts a background spectrum from the corresponding background PET and subtracts the background from the object spectrum.
Also optimal weighting (weights=yes) can be used to enhance the signal-to-noise ratio. Using quantitative contamination is a prerequisite to be able to computing optimal weights.
aXe tasks use default names for input and output files based on the given name of the "grism" image. For this task the default input PET would be called <grism-rootname>_<science extension>.PET.fits and the output SPC file would be <grism-rootname>_<science extension>.SPC.fits.
1. Extract 1D spectra from the PET which was derived from image test_grism_1.fits. To give meaningful (without background) result, the sky background must have been removed from the grism/prism image before creating the PET.
ax> pet2spc test_grism_1.fits SLIM.conf.test.0
2. As in 1., but use the background PET to extract and subtract a background spectrum from the object spectrum. Apply optimal weights in the 1D extraction.
ax> pet2spc test_grism_1.fits SLIM.conf.test.0 use_bpet='yes' weights='yes'
Refer to manual for more detailed information about using this aXe task: