Image Reduction Pipeline
Image “reduction” turns raw data into processed data. Typically the following steps are applied:
Dark/Bias subtraction
Flat fielding
Bad Pixel Correction
Non-linearity correction
tshirt
can apply these steps to common CCD data.
How to Use for Reduction
Edit the Reduction parameters. You can specify any number of directories for reducing data.
Start by reading in the parameters and making calibration files.
from tshirt.pipeline import prep_images
pipeObj = prep_images.prep('parameters/path_to_file.yaml')
pipeObj.makeMasterCals()
After the calibration files look good, apply them to the science data
pipeObj.procSciFiles()