xeofs: Comprehensive EOF analysis in Python withxarray

2024/01/02 by Niclas Rieger, Samuel J. Levang · 1 voice · 1 citation
Earth and Planetary Sciences · Environmental Science · Mathematics · #Geophysics and Gravity Measurements #Climate variability and models #Statistical and numerical algorithms

paper · pdf · doi:10.21105/joss.06060

openalex publication_date 2024/01/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/03

Abstract

xeofs is a Python package tailored for the climate science community, designed to streamline advanced data analysis using dimensionality reduction techniques like Empirical Orthogonal Functions (EOF) analysis -often called Principal Component Analysis (PCA) in other domains.Integrating seamlessly with xarray objects (Hoyer & Hamman, 2017), xeofs makes it easier to analyze large, labeled, multi-dimensional datasets.By harnessing Dask's capabilities (Dask Development Team, 2016), it scales computations efficiently across multiple cores or clusters, apt for extensive climate data applications.

Citations

• The Varimax Criterion for Analytic Rotation in Factor Analysis
• Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions
• Relations Between Two Sets of Variates

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Discussions

• xeofs citation: Rieger, N. & Levang, S. J. (2024). xeofs: Comprehensive EOF analysis in Python with xarray. Journal of Open Source Software, 9(93), 6060. DOI: doi.org/10.21105/jos... [bsky, 0 points, 0 comments]