SciPy 1.0: fundamental algorithms for scientific computing in Python
Authors
Virtanen, Pauli
Oliphant, Travis E.
Cournapeau, David
Burovski, Evgeni
Peterson, Pearu
Weckesser, Warren
Bright, Jonathan
Brett, Matthew
Wilson, Joshua
Mayorov, Nikolay
Jones, Eric
Kern, Robert
Larson, Eric
Carey, C J
Polat, İlhan
Feng, Yu
Moore, Eric W.
VanderPlas, Jake
Perktold, Josef
Cimrman, Robert
Henriksen, Ian
Quintero, E. A.
Harris, Charles R.
Archibald, Anne M.
Pedregosa, Fabian
Vijaykumar, Aditya
Bardelli, Alessandro Pietro
Rothberg, Alex
Hilboll, Andreas
Kloeckner, Andreas
Scopatz, Anthony
Lee, Antony
Rokem, Ariel
Woods, C. Nathan
Fulton, Chad
Masson, Charles
Häggström, Christian
Fitzgerald, Clark
Nicholson, David A.
Hagen, David R.
Pasechnik, Dmitrii V.
Olivetti, Emanuele
Martin, Eric
Wieser, Eric
Silva, Fabrice
Lenders, Felix
Wilhelm, Florian
Young, G.
Price, Gavin A.
Ingold, Gert-Ludwig
Allen, Gregory E.
Lee, Gregory R.
Audren, Hervé
Probst, Irvin
Dietrich, Jörg P.
Silterra, Jacob
Webber, James T
Slavič, Janko
Nothman, Joel
Buchner, Johannes
Kulick, Johannes
Schönberger, Johannes L.
de Miranda Cardoso, José Vinícius
Reimer, Joscha
Harrington, Joseph
Rodríguez, Juan Luis Cano
Nunez-Iglesias, Juan
Kuczynski, Justin
Tritz, Kevin
Thoma, Martin
Newville, Matthew
Kümmerer, Matthias
Bolingbroke, Maximilian
Tartre, Michael
Pak, Mikhail
Smith, Nathaniel J.
Nowaczyk, Nikolai
Shebanov, Nikolay
Pavlyk, Oleksandr
Brodtkorb, Per A.
Lee, Perry
McGibbon, Robert T.
Feldbauer, Roman
Lewis, Sam
Tygier, Sam
Sievert, Scott
Vigna, Sebastiano
Peterson, Stefan
More, Surhud
Pudlik, Tadeusz
Oshima, Takuya
Pingel, Thomas J.
Robitaille, Thomas P.
Spura, Thomas
Jones, Thouis R.
Cera, Tim
Leslie, Tim
Zito, Tiziano
Krauss, Tom
Upadhyay, Utkarsh
Halchenko, Yaroslav O.
Vázquez-Baeza, Yoshiki
Publication Date
2020-02-03Journal Title
Nature Methods
ISSN
1548-7091
Publisher
Nature Publishing Group US
Volume
17
Issue
3
Pages
261-272
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., et al. (2020). SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods, 17 (3), 261-272. https://doi.org/10.1038/s41592-019-0686-2
Abstract
Abstract: SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
Keywords
Perspective, /631/114, /631/45/56, /706/703/559, perspective
Identifiers
s41592-019-0686-2, 686
External DOI: https://doi.org/10.1038/s41592-019-0686-2
This record's URL: https://www.repository.cam.ac.uk/handle/1810/317023
Rights
Attribution 4.0 International (CC BY 4.0)
Licence URL: https://creativecommons.org/licenses/by/4.0/
Statistics
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