Nature· 2020Q1· Review
Array programming with NumPy
- 22,658citations
- Q1SCImago
- 2020year
Short summary
NumPy is the core Python library enabling powerful array programming for scientific data analysis across diverse fields like physics, astronomy, and finance.
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Key points
- NumPy facilitates array programming for efficient data manipulation in vectors, matrices, and higher dimensions.
- It is a foundational library for scientific analysis in fields ranging from physics to finance.
- NumPy played a role in significant discoveries like gravitational waves and black hole imaging.
- It acts as an interoperability layer, connecting various array computation libraries.
AI-generated from the title and abstract; the full text is not read.
Abstract
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 waves 1 and in the first imaging of a black hole 2 . 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.
The authors' abstract, as published at the source. Nature, 2020 · DOI ↗
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Field: Artificial Intelligence
Artificial IntelligenceComputer Science