What’s New in PyWiFeS

This pipeline automates many of the routine tasks involved in data reduction. It is written in Python and is open-source, allowing users to modify and extend the code to suit their needs. PyWiFeS is an automated and upgraded version of the original PyWiFeS pipeline (see documentation here), developed by Childress et al. (2014)

Upgrades from the Previous Version

Main upgrades from the previous PyWiFeS version:

• Updated to Python 3, with bug fixes and headers for the new telescope setup.

• Pip installable.

• Supports various observing configurations automatically:

  • classic mode.

  • nod-and-shuffle mode.

  • sub-nod-and-shuffle mode.

  • Stellar frame configuration (that is, only half of the detector is used).

  • Any single binning mode, plus standards binned differently from science data.

  • Backwards compatible with data obtained by TAROS.

• New JSON5 config files for each grating, with comments for each user option. - The pipeline will choose a template automatically, if not specified by the user. - Users don’t need to set anything to generate metadata or reduction scripts anymore. - Users can create their own JSON5 file following the same structure as their preferred setup.

• Logger file to track data usage and pipeline performance.

• Implemented astrometry in the data cubes. The accuracy could be low (> 2 arcsec) in some cases.

• Extraction and splicing of the spectra and splicing of the 3D astrometrised cubes are now implemented.

• Added multiprocessing for faster execution.

• Multiple quality plots are automatically generated and saved.

• Organized output directory (/data_products), which can be modified by command-line option.

Key Features

• Fully automated data reduction processes.

• Provides tools for quality control and analysis.

• Supports batch processing of multiple objects in a single night.

• Extensible and customizable.