.. _features: 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.