Reduction Instruction for Linear Polarization. Basic version

Here are the steps necessary to reduce linear polarimetric data from RSS with the polsalt package. For the most part, the steps here are automatic with the minimum amount of interaction. If you haven't installed polsalt, follow the Installation of Polsalt instructions to do so. In addition, to installing the packages, you will need the scripts located in the polsalt/scripts package.

1. Unpack your data in the same format it comes from SALT such that the raw data is inside a directory with the observing date in YYYYMMDD format. So for example, your data would be sitting in a 20160708/raw/.

2. Carry out the basic reductions and wavelenth calibration on your data

python scripts/reducepoldata.py 20160708

This will process the data through the basic reductions and also the wavelength calibration. For the wavelength calibration, the specidentify interface will appear for you to identify lines. We suggest doing the manual identification for the first row and once you are happy with the solution on that row and have saved it, the rest of the rows can be auto-identified. The calibration step will occur twice (once for the O-beam and once for the E-beam). Note: when this finishes, there may be a segmentation fault, but it has likely finished fine and that this is due to pyraf closing.

3. The step above would have created a directory called sci in your 20160708 folder. In order to apply the wavelength calibration to the images, you need to be in this folder

python scripts/correct_files.py w*fits

4. Extract the spectrum for each image. Open one of the images in ds9 and determine the center row of the spectra in both the O- and E- beams as well as the half-width of the extraction window.

python scripts/pol_extract.py cwmxgbpP20160708012*.fits --yo 272 --ye 238 --dy 5

5. Create the stokes files

python scripts/pol_stokes.py

6. Plot the results.

python polsalt/specpolview.py *_stokes.fits 100A textplot