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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Effects of UV Stellar Spectral Uncertainty on the Chemistry of Terrestrial Atmospheres
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The impact of mixing treatments on cloud modelling in 3D simulations of hot Jupiters
Duncan Christie,Nathan J. Mayne,Stefan Lines,Stefan Lines,Vivien Parmentier,James Manners,Ian A. Boutle,Ian A. Boutle,Ben Drummond,Ben Drummond,Thomas Mikal-Evans,David K. Sing,Krisztian Kohary +12 more
TL;DR: In this article, the role of mixing by replacing the default convective treatment used in previous works with a more physically relevant mixing treatment based on global circulation is investigated, and it is shown that uncertainty in the efficiency of sedimentation through the sedimentation factor plays a larger role in shaping cloud thickness and its radiative feedback on the local gas temperatures than the switch in mixing treatment.
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Correction to: Optical variability of quasars with 20-year photometric light curves
Zach Stone,Yue-Long Shen,Colin J. Burke,Yu Ching Chen,Qian Yang,Xin Liu,Robert A. Gruendl,Monika Adamów,F. Andrade-Oliveira,James Annis,David Bacon,E. Bertin,Sebastian Bocquet,David J. Brooks,D. L. Burke,A. Carnero Rosell,M. Carrasco Kind,J. Carretero,Luiz N. da Costa,Maria E. S. Pereira,J. De Vicente,Shantanu Desai,H. T. Diehl,Peter Doel,I. Ferrero,Douglas N. Friedel,Joshua A. Frieman,J. Garc'ia-Bellido,Enrique Gaztanaga,Daniel Gruen,G. Gutierrez,Samuel Hinton,D. L. Hollowood,K. Honscheid,Kyler Kuehn,Nikolay Kuropatkin,C. Lidman,Marcio A. G. Maia,Felipe Menanteau,Ramon Miquel,Robert Morgan,F. Paz-Chinch'on,Adriano Pieres,A. P. Malag'on,Mario Rodríguez-Monroy,E. Sánchez,V. Scarpine,S. Serrano,I. Sevilla-Noarbe,E. Suchyta,Molly E. C. Swanson,Gregory Tarle,C. T. D. O. Astronomy,U. O. I. Urbana-Champaign,National Center for Supercomputing Applications,Center for Astrophysical Surveys,H. C. F. Astrophysics,Instituto de F'isica Te'orica,Universidade Estadual Paulista,L. LIneA,F. N. Laboratory,Institute of Cosmology,Gravitation,U. Portsmouth,Cnrs,Umr 7095,I. Paris,Sorbonne Universit'es,06 UPMCUnivParis,F. O. Physics,Ludwig-Maximilians-Universität,D. PhysicsAstronomy,University College London,Kavli Institute for Particle AstrophysicsCosmology,Slac National Accelerator Laboratory,Institut de F'isica d'Altes Energies,T. Science,Technology,Observatório Nacional,D. Physics,U.o. Michigan,Ann Arbor,Hamburger Sternwarte,U. Hamburg,Centro de Investigaciones Energ'eticas,Medioambientales y Tecnol'ogicas,Iit Hyderabad,Institute of Theoretical Astrophysics,Universityof Oslo,Instituto de Fisica Teorica Uamcsic,U. A. D. Madrid,Institut d'Estudis Espacials de Catalunya,Institute for Space Sciences,Campus Uab,S. O. Mathematics,Physics,Universityof Queensland,Santa Cruz Institute for Particle Physics,Center for Cosmology,Astro-particle Physics,T. O. S. University,Australian Astronomical Optics,M. University,L. Observatory,Centre for Gravitational Astrophysics,College of Materials Science,The Australian National University,T. N. D. O. Astronomy,Astrophysics,A. N. University,Instituci'o Catalana de Recerca i Estudis Avanccats,P. Department,Universityof Wisconsin-Madison,I. O. Astronomy,Universityof Cambridge,Department of Astrophysical Sciences,P. University,Computer Science,M. Division,Oak Ridge National Laboratory,Waldorf High School of Massachusetts Bay +120 more
TL;DR: In this paper , the authors studied the optical variability of a sample of 190 quasars within the SDSS Stripe 82 region that have long-term photometric coverage during 1998-2020.
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Structural Analysis of Nanoscale Network Materials Using Graph Theory.
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Label-free identification of microplastics in human cells: dark-field microscopy and deep learning study.
TL;DR: In this paper, a residual neural network (ResNet) was used to classify polystyrene microparticles using enhanced dark-field microscopy and residual neural networks (RNNs).
References
More filters
Journal Article
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
TL;DR: Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems, focusing on bringing machine learning to non-specialists using a general-purpose high-level language.
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
TL;DR: Scikit-learn as mentioned in this paper is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems.
Journal ArticleDOI
Matplotlib: A 2D Graphics Environment
TL;DR: Matplotlib is a 2D graphics package used for Python for application development, interactive scripting, and publication-quality image generation across user interfaces and operating systems.
Journal ArticleDOI
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
TL;DR: SciPy as discussed by the authors is an open source scientific computing library for the Python programming language, which includes functionality spanning clustering, Fourier transforms, integration, interpolation, file I/O, linear algebra, image processing, orthogonal distance regression, minimization algorithms, signal processing, sparse matrix handling, computational geometry, and statistics.
Proceedings ArticleDOI
TensorFlow: a system for large-scale machine learning
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
TL;DR: TensorFlow as mentioned in this paper is a machine learning system that operates at large scale and in heterogeneous environments, using dataflow graphs to represent computation, shared state, and the operations that mutate that state.
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