Treffer: reciprocalspaceship : a Python library for crystallographic data analysis.

Title:
reciprocalspaceship : a Python library for crystallographic data analysis.
Authors:
Greisman JB; Department of Molecular and Cellular Biology, Harvard University, 52 Oxford Street, Cambridge, MA 02138, USA., Dalton KM; Department of Molecular and Cellular Biology, Harvard University, 52 Oxford Street, Cambridge, MA 02138, USA., Hekstra DR; Department of Molecular and Cellular Biology, Harvard University, 52 Oxford Street, Cambridge, MA 02138, USA.; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA.
Source:
Journal of applied crystallography [J Appl Crystallogr] 2021 Sep 04; Vol. 54 (Pt 5), pp. 1521-1529. Date of Electronic Publication: 2021 Sep 04 (Print Publication: 2021).
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Wiley Online Library Country of Publication: United States NLM ID: 9876190 Publication Model: eCollection Cited Medium: Print ISSN: 0021-8898 (Print) Linking ISSN: 00218898 NLM ISO Abbreviation: J Appl Crystallogr Subsets: PubMed not MEDLINE
Imprint Name(s):
Publication: [Malden, MA] : Wiley Online Library
Original Publication: Copenhagen, Munksgaard International Booksellers and Publishers.
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Grant Information:
P30 GM124165 United States GM NIGMS NIH HHS; P41 GM118217 United States GM NIGMS NIH HHS
Contributed Indexing:
Keywords: Python; X-ray crystallography; data analysis
Entry Date(s):
Date Created: 20211021 Latest Revision: 20240529
Update Code:
20250114
PubMed Central ID:
PMC8493618
DOI:
10.1107/S160057672100755X
PMID:
34671231
Database:
MEDLINE

Weitere Informationen

Crystallography uses the diffraction of X-rays, electrons or neutrons by crystals to provide invaluable data on the atomic structure of matter, from single atoms to ribosomes. Much of crystallography's success is due to the software packages developed to enable automated processing of diffraction data. However, the analysis of unconventional diffraction experiments can still pose significant challenges - many existing programs are closed source, sparsely documented, or challenging to integrate with modern libraries for scientific computing and machine learning. Described here is reciprocalspaceship , a Python library for exploring reciprocal space. It provides a tabular representation for reflection data from diffraction experiments that extends the widely used pandas library with built-in methods for handling space groups, unit cells and symmetry-based operations. As is illustrated, this library facilitates new modes of exploratory data analysis while supporting the prototyping, development and release of new methods.
(© Jack B. Greisman et al. 2021.)