GradPak_scat

A quick and non-so-dirty scattered light correction designed for GradPak data. You’ll need this because IRAF’s scatter light routines cannot deal with the very small gaps between the fibers.

The algorithm is simple. For each wavelength channel the “scattered light” is just a linear interpolation of the average of the dark regions beyond the edges of the slit. Essentially it finds the light scattered by the edge fibers and interpolates it across the whole slit. It’s not perfect, but it’s better than nothing and it works.

The calling syntax is:

> python GradPak_scat.py input.lst output.lst

where input.lst and output.lst contain the names of the input and output fits files, one on each line. If you’ve ever used @lists in IRAF you will understand what is required here.

Warning

The pixel locations of the off-slit dark regions is currently hardcoded based on a 2x2 binning scheme. If you didn’t use 2x2 binning this will not work as expected.

Functions

GradPak_scat.do_multi(inputs, outputs)

Read input and output files and run GradPak_scat.do_single() on each pair

Very simple; just read the lines and run the main function. The only little hiccup is that readlines() keeps the newline characters around in the names so we need to nuke those.

Parameters:

inputs : str

Name of the file containing input image names, one per line

outputs : str

Name of the file containing output image names, one per line
Returns:

None
GradPak_scat.do_single(input_image, output_image)

Perform a GradPak scattered light correction on a single image.

First compute the mean “gutter” (the regions beyond the edges of the slit) spectrum, then interpolated between the two gutters at each wavelength. Finally, subtract this interpolated image from the input and write the results to the output file.

Parameters:

input_image : str

Name of the input FITS image

output_image : str

Name of the file to contain the scattered light corrected FITS image
Returns:

None

Notes

Currently hardwired for 2x2 binning. Will likely work in any case where binning in the spatial dimension is 2, but this has not been tested.