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
Reads0
Chats0
TLDR
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
Citations
More filters
Posted Content
The ITensor Software Library for Tensor Network Calculations
TL;DR: The philosophy behind ITensor, a system for programming tensor network calculations with an interface modeled on tensor diagram notation, and examples of each part of the interface including Index objects, the ITensor product operator, Tensor factorizations, tensor storage types, algorithms for matrix product state (MPS) and matrix product operator (MPO) tensor networks, and the NDTensors library are discussed.
Journal ArticleDOI
Tests of general relativity with binary black holes from the second LIGO-Virgo gravitational-wave transient catalog
O. Edy,I. W. Harry,Andrew Lundgren,C. McIsaac,Simone Mozzon,L. K. Nuttall,A. E. Tolley,A. R. Williamson +7 more
TL;DR: In this article, the authors evaluate the consistency of the LIGO-Virgo data with predictions from the theory and find no evidence for new physics beyond general relativity, for black hole mimickers, or for any unaccounted systematics.
Journal ArticleDOI
gmx_MMPBSA: A New Tool to Perform End-State Free Energy Calculations with GROMACS.
Mario S. Valdés-Tresanco,Mario E. Valdés-Tresanco,Pedro A. Valiente,Pedro A. Valiente,Ernesto Moreno +4 more
TL;DR: Gmx_MMPBSA as discussed by the authors is a new tool to perform end-state free energy calculations from GROMACS molecular dynamics trajectories, which provides the user with several options, including bounding free energy calculation with different solvation models (PB, GB, or 3D-RISM), stability calculations, computational alanine scanning, entropy corrections, and binding free energy decomposition.
Journal ArticleDOI
The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package
The Astropy Collaboration,Adrian M. Price-Whelan,Pey Lian Lim,Nicholas Earl,Nathaniel Starkman,Larry Bradley,David L. Shupe,Aarya A. Patil,Lia Corrales,C. E. Brasseur,M. Nöthe,Axel Donath,Erik Tollerud,Brett M. Morris,Adam Ginsburg,Eero Vaher,B. A. Weaver,James Tocknell,William Jamieson,M. H. van Kerkwijk,Thomas P. Robitaille,Bruce Merry,Matteo Bachetti,H. M. Gunther,Tom Aldcroft,Jaime A. Alvarado-Montes,Anne M. Archibald,A. B'odi,Shreyas Bapat,Geert Barentsen,Juanjo Baz'an,Manish J Biswas,Médéric Boquien,D. J. Burke,D Di Cara,Mihai Cara,Kyle E. Conroy,Simon Conseil,Matt Craig,Robert M. Cross,Kelle L. Cruz,Francesco D'Eugenio,Nadia Dencheva,Hadrien A. R. Devillepoix,J. P. Dietrich,Arthur Eigenbrot,Thomas Erben,Leonardo Ferreira,Daniel Foreman-Mackey,R. T. Fox,Nabil Freij,Suyog Garg,Robel Geda,Lauren Glattly,Yash Gondhalekar,Karl D. Gordon,David Grant,Perry Greenfield,A. M. Groener,S. Guest,Sebastián Gurovich,Rasmus Handberg,Akeem Hart,Zac Hatfield-Dodds,Derek Homeier,Griffin Hosseinzadeh,Tim Jenness,Craig Jones,Prajwel Joseph,J. Bryce Kalmbach,Emir Karamehmetoglu,M. Kaluszy'nski,Michaelann Kelley,Nicholas S. Kern,Wolfgang Kerzendorf,Eric W. Koch,Shankar Kulumani,Antony H. Lee,Chun Ly,Zhiyuan Mao,Conor D. MacBride,Jakob M. Maljaars,Demitri Muna,Nellie Appy Murphy,Henrik Norman,R. G. O'Steen,Kyle A. Oman,Camilla Pacifici,Sergio Pascual,J. Pascual-Granado,Rohit R Patil,G. I. Perren,T. E. Pickering,Tanuja Rastogi,Benjamin R. Roulston,Daniel F Ryan,Eli S. Rykoff,J. Sabater,Parikshit Sakurikar,Jesús Busto Salgado,Aniket Sanghi,Nicholas Saunders,V. G. Savchenko,L. C. Schwardt,Michael Seifert-Eckert,Albert J. Shih,A. S. Jain,G. R. Shukla,J. Sick,Chris Simpson,Sudheesh Singanamalla,Leo Singer,Jaladh Singhal,Manodeep Sinha,B. SipHocz,Lee R. Spitler,David Stansby,Ole Streicher,Jani vSumak,John D. Swinbank,Dan S. Taranu,N. B. Tewary,Grant R. Tremblay,Miguel De Val-Borro,Samuel J. Van Kooten,Zlatan Vasovi'c,Shresth Verma,José Vinícius de Miranda Cardoso,Peter K. G. Williams,Tom J. Wilson,Benjamin Winkel,W. M. Wood-Vasey,Rui Xue,Peter Yoachim,Chenchen Zhang,Andrea Zonca +135 more
TL;DR: Astropy as mentioned in this paper is a Python package that provides commonly needed functionality to the astronomical community, such as astronomy, astronomy, and astronomy data visualization, as well as other related projects and packages.
Journal ArticleDOI
NeuroKit2: A Python toolbox for neurophysiological signal processing
Dominique Makowski,Tam Pham,Zen J. Lau,Jan C. Brammer,François Lespinasse,Hung Pham,Christopher Schölzel,S. H. Annabel Chen +7 more
TL;DR: NeuroKit2 as discussed by the authors is an open-source, community-driven, and user-centered Python package for neurophysiological signal processing, which includes high-level functions that enable data processing in a few lines of code using validated pipelines.
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.
Related Papers (5)
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
Astropy: A community Python package for astronomy
Thomas P. Robitaille,Erik Tollerud,Perry Greenfield,Michael Droettboom,Erik Bray,Tom Aldcroft,Matt Davis,Adam Ginsburg,Adrian M. Price-Whelan,Wolfgang Kerzendorf,A. Conley,Neil H. M. Crighton,Kyle Barbary,Demitri Muna,Henry C. Ferguson,Frédéric Grollier,Madhura Parikh,Prasanth H. Nair,Hans Moritz Günther,Christoph Deil,Julien Woillez,Simon Conseil,Roban Kramer,J. Turner,Leo Singer,R. T. Fox,Benjamin A. Weaver,Victor Zabalza,Zachary I. Edwards,K. Azalee Bostroem,Douglas Burke,Andrew R. Casey,Steven M. Crawford,Nadia Dencheva,Justin Ely,Tim Jenness,Kathleen Labrie,Pey Lian Lim,Francesco Pierfederici,Andrew Pontzen,Andy Ptak,Brian L. Refsdal,Mathieu Servillat,Ole Streicher +43 more