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()

Contents:

• Image Reduction Pipeline
• Reduction Parameters