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dc.contributor.authorHarris, Charles R.
dc.contributor.authorMillman, K. Jarrod
dc.contributor.authorvan der Walt, Stéfan J.
dc.contributor.authorGommers, Ralf
dc.contributor.authorVirtanen, Pauli
dc.contributor.authorCournapeau, David
dc.contributor.authorWieser, Eric
dc.contributor.authorTaylor, Julian
dc.contributor.authorBerg, Sebastian
dc.contributor.authorSmith, Nathaniel J.
dc.contributor.authorKern, Robert
dc.contributor.authorPicus, Matti
dc.contributor.authorHoyer, Stephan
dc.contributor.authorvan Kerkwijk, Marten H.
dc.contributor.authorBrett, Matthew
dc.contributor.authorHaldane, Allan
dc.contributor.authordel Río, Jaime Fernández
dc.contributor.authorWiebe, Mark
dc.contributor.authorPeterson, Pearu
dc.contributor.authorGérard-Marchant, Pierre
dc.contributor.authorSheppard, Kevin
dc.contributor.authorReddy, Tyler
dc.contributor.authorWeckesser, Warren
dc.contributor.authorAbbasi, Hameer
dc.contributor.authorGohlke, Christoph
dc.contributor.authorOliphant, Travis E.
dc.date.accessioned2020-12-24T16:09:10Z
dc.date.available2020-12-24T16:09:10Z
dc.date.issued2020-09-16
dc.date.submitted2020-02-21
dc.identifier.issn0028-0836
dc.identifier.others41586-020-2649-2
dc.identifier.other2649
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/315595
dc.description.abstractAbstract: Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis.
dc.languageen
dc.publisherNature Publishing Group UK
dc.rightsAttribution 4.0 International (CC BY 4.0)en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectReview Article
dc.subject/631/378/116
dc.subject/704/525/870
dc.subject/639/705/1042
dc.subject/639/705/117
dc.subject/639/705/794
dc.subject/139
dc.subjectreview-article
dc.titleArray programming with NumPy
dc.typeArticle
dc.date.updated2020-12-24T16:09:09Z
prism.endingPage362
prism.issueIdentifier7825
prism.publicationNameNature
prism.startingPage357
prism.volume585
dc.identifier.doi10.17863/CAM.62701
dcterms.dateAccepted2020-06-17
rioxxterms.versionofrecord10.1038/s41586-020-2649-2
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidMillman, K. Jarrod [0000-0002-5263-5070]
dc.contributor.orcidvan der Walt, Stéfan J. [0000-0001-9276-1891]
dc.contributor.orcidGommers, Ralf [0000-0002-0300-3333]
dc.contributor.orcidPicus, Matti [0000-0002-1771-9949]
dc.contributor.orcidHoyer, Stephan [0000-0002-5207-0380]
dc.contributor.orcidWiebe, Mark [0000-0003-3603-8038]
dc.contributor.orcidPeterson, Pearu [0000-0001-7328-4305]
dc.contributor.orcidSheppard, Kevin [0000-0001-8700-2292]
dc.contributor.orcidGohlke, Christoph [0000-0001-8108-7707]
dc.identifier.eissn1476-4687


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's licence is described as Attribution 4.0 International (CC BY 4.0)