论文标题
带有numpy的数组编程
Array Programming with NumPy
论文作者
论文摘要
阵列编程提供了一种功能强大的，紧凑的表达语法，用于访问，操纵和操作向量，矩阵和高维数组中的数据。 Numpy是Python语言的主要数组编程库。它在研究分析管道中起着重要作用，例如物理，化学，天文学，地球科学，生物学，心理学，材料科学，工程，金融和经济学等多样化的领域。例如，在天文学中，Numpy是在发现引力波和黑洞的首次成像中使用的软件堆栈的重要组成部分。在这里，我们展示了一些基本阵列概念如何导致一个简单而强大的编程范式，用于组织，探索和分析科学数据。 Numpy是整个科学Python宇宙的基础。这是如此普遍，以至于针对具有专业需求的受众的几个项目已经开发了自己的类似Numpy的界面和数组对象。由于其在生态系统中的中心位置，Numpy越来越多地在这些新数组计算库之间扮演着互操作层的作用。
Array programming provides a powerful, compact, 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 plays an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, material science, engineering, finance, and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves and the first imaging of a black hole. Here we show how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring, and analyzing scientific data. NumPy is the foundation upon which the entire scientific Python universe is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Because of its central position in the ecosystem, NumPy increasingly plays the role of an interoperability layer between these new array computation libraries.
