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Open AccessJournal ArticleDOI

The Astropy Project: Building an Open-science Project and Status of the v2.0 Core Package

Adrian M. Price-Whelan, +138 more
- 24 Aug 2018 - 
- Vol. 156, Iss: 3, pp 123-123
TLDR
The Astropy project as discussed by the authors is a Python project supporting the development of open-source and openly developed Python packages that provide commonly needed functionality to the astronomical community, including the core package astropy.
Abstract
The Astropy Project supports and fosters the development of open-source and openly developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the Astropy Project is the core package astropy, which serves as the foundation for more specialized projects and packages. In this article, we provide an overview of the organization of the Astropy project and summarize key features in the core package, as of the recent major release, version 2.0. We then describe the project infrastructure designed to facilitate and support development for a broader ecosystem of interoperable packages. We conclude with a future outlook of planned new features and directions for the broader Astropy Project.

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Journal ArticleDOI

SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python

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.
Journal ArticleDOI

SciPy 1.0: fundamental algorithms for scientific computing in Python.

TL;DR: SciPy as discussed by the authors is an open-source scientific computing library for the Python programming language, which 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.
Journal ArticleDOI

GW190425: Observation of a Compact Binary Coalescence with Total Mass ∼ 3.4 M O

B. P. Abbott, +1274 more
TL;DR: In 2019, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9 and the Virgo detector was also taking data that did not contribute to detection due to a low SINR but were used for subsequent parameter estimation as discussed by the authors.
References
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Journal ArticleDOI

Planck 2015 results - XIII. Cosmological parameters

Peter A. R. Ade, +337 more
TL;DR: In this article, the authors present a cosmological analysis based on full-mission Planck observations of temperature and polarization anisotropies of the cosmic microwave background (CMB) radiation.
Journal ArticleDOI

Planck 2015 results. XIII. Cosmological parameters

Peter A. R. Ade, +260 more
TL;DR: In this paper, the authors present results based on full-mission Planck observations of temperature and polarization anisotropies of the CMB, which are consistent with the six-parameter inflationary LCDM cosmology.
Journal ArticleDOI

Astropy: A community Python package for astronomy

TL;DR: Astropy as discussed by the authors is a Python package for astronomy-related functionality, including support for domain-specific file formats such as flexible image transport system (FITS) files, Virtual Observatory (VO) tables, common ASCII table formats, unit and physical quantity conversions, physical constants specific to astronomy, celestial coordinate and time transformations, world coordinate system (WCS) support, generalized containers for representing gridded as well as tabular data, and a framework for cosmological transformations and conversions.
Journal ArticleDOI

The NumPy Array: A Structure for Efficient Numerical Computation

TL;DR: In this article, the authors show how to improve the performance of NumPy arrays through vectorizing calculations, avoiding copying data in memory, and minimizing operation counts, which is a technique similar to the one described in this paper.
Journal ArticleDOI

Studies in astronomical time series analysis. II - Statistical aspects of spectral analysis of unevenly spaced data

TL;DR: This paper studies the reliability and efficiency of detection with the most commonly used technique, the periodogram, in the case where the observation times are unevenly spaced to retain the simple statistical behavior of the evenly spaced case.
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