Array programming with NumPy
Charles R. Harris,K. Jarrod Millman,Stefan van der Walt,Stefan van der Walt,Ralf Gommers,Pauli Virtanen,David Cournapeau,Eric Wieser,Julian Taylor,Sebastian Berg,Nathaniel J. Smith,Robert Kern,Matti Picus,Stephan Hoyer,Marten H. van Kerkwijk,Matthew Brett,Matthew Brett,Allan Haldane,Jaime Fernández del Río,Mark Wiebe,Mark Wiebe,Pearu Peterson,Pierre Gérard-Marchant,Kevin Sheppard,Tyler Reddy,Warren Weckesser,Hameer Abbasi,Christoph Gohlke,Travis E. Oliphant +28 more
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In this paper, the authors review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data, and their evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.Abstract:
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. NumPy is the primary array programming library for Python; here its fundamental concepts are reviewed and its evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.read more
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ARMADA I: Triple Companions Detected in B-Type Binaries alpha Del and nu Gem
Tyler Gardner,John D. Monnier,Francis C. Fekel,Gail Schaefer,Keith J.C. Johnson,Jean-Baptiste Le Bouquin,Stefan Kraus,Narsireddy Anugu,Benjamin R. Setterholm,Aaron Labdon,Claire L. Davies,Cyprien Lanthermann,Jacob Ennis,Michael J. Ireland,Kaitlin M. Kratter,T. ten Brummelaar,Judit Sturmann,Laszlo Sturmann,Chris Farrington,Douglas R. Gies,Robert Klement,Fred C. Adams +21 more
TL;DR: The ARMADA survey as discussed by the authors uses the MIRC-X instrument at the CHARA array for the purpose of detecting giant planets and stellar companions orbiting individual stars in binary systems, where the wavelength calibration scheme that delivers precision at the tens of micro-arcseconds level for < 0.2 arcsecond binaries is introduced.
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A Decade of Radial-velocity Monitoring of Vega and New Limits on the Presence of Planets
Spencer A. Hurt,Samuel N. Quinn,David W. Latham,Andrew Vanderburg,Gilbert A. Esquerdo,Michael L. Calkins,Perry Berlind,Ruth Angus,Christian A. Latham,George Zhou +9 more
TL;DR: In this paper, the authors present an analysis of 1524 spectra of Vega spanning 10 years, in which they search for periodic radial velocity variations and detect a candidate radial velocity signal with a period of 2.43 days and a semi-amplitude of 6 m/s.
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Explosion analysis from images: Trinity and Beirut
TL;DR: In this article, the authors applied the method originally developed to study the first nuclear detonation and analyzed the Trinity blast data, the method is applied to the Beirut explosion of August 2020 by using images from videos posted online.
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A Criterion for the Onset of Chaos in Compact, Eccentric Multiplanet Systems
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Solar Flare Effects on the Earth’s Lower Ionosphere
TL;DR: In this article, a large-scale statistical study of 334 solar-flare events and their impacts on the D-region over the past solar cycle is presented, focusing on both GOES broadband X-ray channels and VLF amplitudes.
References
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Scikit-learn: Machine Learning in Python
Fabian Pedregosa,Gaël Varoquaux,Alexandre Gramfort,Vincent Michel,Bertrand Thirion,Olivier Grisel,Mathieu Blondel,Peter Prettenhofer,Ron Weiss,Vincent Dubourg,Jake Vanderplas,Alexandre Passos,David Cournapeau,Matthieu Brucher,Matthieu Perrot,Edouard Duchesnay +15 more
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Posted Content
Scikit-learn: Machine Learning in Python
Fabian Pedregosa,Gaël Varoquaux,Alexandre Gramfort,Vincent Michel,Bertrand Thirion,Olivier Grisel,Mathieu Blondel,Andreas Müller,Joel Nothman,Gilles Louppe,Peter Prettenhofer,Ron Weiss,Vincent Dubourg,Jake Vanderplas,Alexandre Passos,David Cournapeau,Matthieu Brucher,Matthieu Perrot,Edouard Duchesnay +18 more
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Matplotlib: A 2D Graphics Environment
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SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
Pauli Virtanen,Ralf Gommers,Travis E. Oliphant,Matt Haberland,Matt Haberland,Tyler Reddy,David Cournapeau,Evgeni Burovski,Pearu Peterson,Warren Weckesser,Jonathan Bright,Stefan van der Walt,Matthew Brett,Joshua Wilson,K. Jarrod Millman,Nikolay Mayorov,Andrew Nelson,Eric Jones,Robert Kern,Eric B. Larson,CJ Carey,Ilhan Polat,Yu Feng,Eric Moore,Jake Vanderplas,Denis Laxalde,Josef Perktold,Robert Cimrman,Ian Henriksen,Ian Henriksen,E. A. Quintero,Charles R. Harris,Anne M. Archibald,Antônio H. Ribeiro,Fabian Pedregosa,Paul van Mulbregt,SciPy . Contributors +36 more
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Martín Abadi,Paul Barham,Jianmin Chen,Zhifeng Chen,Andy Davis,Jeffrey Dean,Matthieu Devin,Sanjay Ghemawat,Geoffrey Irving,Michael Isard,Manjunath Kudlur,Josh Levenberg,Rajat Monga,Sherry Moore,Derek G. Murray,Benoit Steiner,Paul A. Tucker,Vijay K. Vasudevan,Pete Warden,Martin Wicke,Yuan Yu,Xiaoqiang Zheng +21 more
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