Pipeline to process ROBO43 data
This repository contains a set o modules to process the ROBO43 photometric data. The modules are written in Python and use various libraries such as NumPy, SciPy, and Astropy.
The module make_thumb.py produces a thumbnail image from a FITS file for a quick look.
The module collect_night_info.py collects the night information from the FITS headers and saves it to a CSV file.
The module make_calibration_frames.py creates master calibration frames (bias, dark, flat) from a set of raw calibration frames.
The module process_robo43_frames.py processes the raw science frames using the master calibration frames and performs astrometric calibration.
Module coadd_frames.py coadds multiple weighted science frames to improve the signal-to-noise ratio.
Module make_coloured_images.py creates coloured images from the processed science frames.
- Add more documentation and examples
- Add module to gather the photometry
- Add more diagnostic plots
- Improve the astrometric calibration
- Add dark frame scaling based on temperature and exposure time
- Create hot pixel mask
The following example image from the Eta Car Nebula was obtained using the ROBO43 telescope and processed using this pipeline:
