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Author Correction: SciPy 1.0: fundamental algorithms for scientific computing in Python.

Virtanen, Pauli; Gommers, Ralf; Oliphant, Travis E; Haberland, Matt; Reddy, Tyler; Cournapeau, David; Burovski, Evgeni; Peterson, Pearu; Weckesser, Warren; Bright, Jonathan; van der Walt, Stéfan J; Brett, Matthew; Wilson, Joshua; Millman, K Jarrod; Mayorov, Nikolay; Nelson, Andrew R J; Jones, Eric; Kern, Robert; Larson, Eric; Carey, C J; Polat, Ilhan; Feng, Yu; Moore, Eric W; VanderPlas, Jake; Laxalde, Denis; Perktold, Josef; Cimrman, Robert; Henriksen, Ian; Quintero, E A; Harris, Charles R; Archibald, Anne M; Ribeiro, Antônio H; Pedregosa, Fabian; van Mulbregt, Paul.

Nat Methods ; 17(3): 352, 2020 03.

Artículo en Inglés | MEDLINE | ID: mdl-32094914

RESUMEN

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

SciPy 1.0: fundamental algorithms for scientific computing in Python.

Nat Methods ; 17(3): 261-272, 2020 03.

Artículo en Inglés | MEDLINE | ID: mdl-32015543

RESUMEN

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.

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Algoritmos , Biología Computacional/métodos , Lenguajes de Programación , Programas Informáticos , Biología Computacional/historia , Simulación por Computador , Historia del Siglo XX , Historia del Siglo XXI , Modelos Lineales , Modelos Biológicos , Dinámicas no Lineales , Procesamiento de Señales Asistido por Computador

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