The PyKOALA python library: a multi-instrument package for IFS data reduction
Pablo Corcho-Caballero, Yago Ascasibar, \'Angel R. L\'opez-S\'anchez, Miguel Gonz\'alez-Bolivar, Nuria P. F. Lorente, James Tocknell, Felipe Jim\'enez-Ibarra, Praveen Jayasuriya Daluwathumullagamage, Gabriella Quattropani, Matt Owers, and Gijs A. Verdoes-Kleijn
TL;DR
PyKOALA is a versatile Python library that streamlines the reduction of IFS data across different instruments, making the process more accessible and efficient for astronomers.
Contribution
The paper introduces PyKOALA, a new instrument-agnostic Python package that simplifies IFS data reduction workflows.
Findings
Successfully applied to KOALA+AAOmega data
Reduces complexity of IFS data processing
Enhances user-friendliness and flexibility
Abstract
PyKOALA is an innovative Python-based library designed to provide a robust and flexible framework for Integral Field Spectroscopy (IFS) data reduction. By addressing the complexities of transforming raw measurements into scientifically valuable spectra, PyKOALA simplifies the data reduction pipeline while remaining instrument-agnostic and user-friendly. This proceeding outlines the challenges of IFS data reduction, PyKOALA's architecture, and its applications to observations by the KOALA+AAOmega instruments at the Anglo-Australian Telescope.
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Taxonomy
TopicsFault Detection and Control Systems