Ichor: A Python library for computational chemistry data management and machine learning force field development.

Autor: Manchev YT; Department of Chemistry, The University of Manchester, Manchester, UK., Burn MJ; Department of Chemistry, The University of Manchester, Manchester, UK., Popelier PLA; Department of Chemistry, The University of Manchester, Manchester, UK.
Jazyk: angličtina
Zdroj: Journal of computational chemistry [J Comput Chem] 2024 Dec 15; Vol. 45 (32), pp. 2912-2928. Date of Electronic Publication: 2024 Aug 31.
DOI: 10.1002/jcc.27477
Abstrakt: We present ichor, an open-source Python library that simplifies data management in computational chemistry and streamlines machine learning force field development. Ichor implements many easily extensible file management tools, in addition to a lazy file reading system, allowing efficient management of hundreds of thousands of computational chemistry files. Data from calculations can be readily stored into databases for easy sharing and post-processing. Raw data can be directly processed by ichor to create machine learning-ready datasets. In addition to powerful data-related capabilities, ichor provides interfaces to popular workload management software employed by High Performance Computing clusters, making for effortless submission of thousands of separate calculations with only a single line of Python code. Furthermore, a simple-to-use command line interface has been implemented through a series of menu systems to further increase accessibility and efficiency of common important ichor tasks. Finally, ichor implements general tools for visualization and analysis of datasets and tools for measuring machine-learning model quality both on test set data and in simulations. With the current functionalities, ichor can serve as an end-to-end data procurement, data management, and analysis solution for machine-learning force-field development.
(© 2024 The Author(s). Journal of Computational Chemistry published by Wiley Periodicals LLC.)
Databáze: MEDLINE
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