eofs: A Library for EOF Analysis of Meteorological, Oceanographic, and Climate Data | Zendy

Andrew Dawson | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

eofs: A Library for EOF Analysis of Meteorological, Oceanographic, and Climate Data

Author(s) -

Andrew Dawson

Publication year - 2016

Publication title -

journal of open research software

Language(s) - English

Resource type - Journals

ISSN - 2049-9647

DOI - 10.5334/jors.122

Subject(s) - python (programming language) , empirical orthogonal functions , computer science , metadata , modular design , software , correctness , netcdf , usability , toolbox , confusion , software engineering , world wide web , programming language , operating system , psychology , machine learning , psychoanalysis

The eofs library provides a high-level Python interface for computing empirical orthogonal functions (EOFs) and related quantities, with a focus on correctness and ease of use. The library is implemented in a modular hierarchical fashion, allowing computations using plain arrays, or the inclusion of metadata. The software provides a convenient package for users wanting to perform EOF analysis in Python, and integrates with popular libraries from atmospheric and climate science. The software is available on Github

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research