{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/pyequib-python-package-an-addendum-to","title":"pyEQUIB Python Package, an addendum to proEQUIB: IDL Library for Plasma Diagnostics and Abundance Analysis","arxiv_id":"2410.13998","date":"2024-10-17","proceeding":null,"authors":["A. Danehkar"],"abstract":"The emission lines from ionized nebulae allow us to determine their physical and chemical properties, along with the interstellar extinction. \"pyEQUIB\" is a pure Python open-source package including several application programming interface (API) functions that can be employed for plasma diagnostics, abundance analysis of collisionally excited lines (CEL) and recombination lines (RL) in nebular astrophysics, and extinction analysis of Balmer lines. This package implements the IDL library \"proEQUIB\" in Python and couples it with the \"AtomNeb\" Python package. This package relies on the Python packages NumPy and SciPy. The API functions of this package can be used for studies of ionized nebulae by astronomers who are familiar with the high-level, general-purpose programming language Python.","url_abs":"https://arxiv.org/abs/2410.13998v1","url_pdf":"https://arxiv.org/pdf/2410.13998v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"pyequib-python-package-an-addendum-to","repo_url":"https://github.com/equib/pyequib","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}