eofs
The facts below are what the maker publishes about eofs, checked and dated. Our editors have not written about it yet.
The facts
Each one read from eofs's own pages, with the date it was checked.
What it does
- Analysis outputs
- Solver methods return EOFs, principal component time series, eigenvalues, variance fractions, and reconstructed fields, among other quantities.checked 8 Oct 2026
- Bayesian analysis
- Nochecked 24 Sep 2026
- Citation
- The project asks users of eofs in published research to cite its peer-reviewed paper and optionally a version-specific Zenodo DOI.checked 8 Oct 2026
- Data import formats
- NetCDF via Iris example; NumPy arrays; xarray objectschecked 24 Sep 2026
- Data interfaces
- The package provides interfaces for NumPy and Dask arrays, plus metadata-enabled interfaces for Iris and xarray.checked 8 Oct 2026
- Dependencies
- NumPy is required; dask is optional, while Iris and xarray are needed only for their respective metadata interfaces.checked 8 Oct 2026
- Deployment
- desktopchecked 24 Sep 2026
- Examples
- The documentation includes standard, Iris, and xarray examples for North Atlantic Oscillation and El Niño analyses.checked 8 Oct 2026
- Implementation
- The implementation is pure Python using NumPy and has no Fortran or C dependencies.checked 8 Oct 2026
- Installation
- The project documents installation through conda-forge, pip, or a source archive.checked 8 Oct 2026
- Intended use
- The package is presented for analyzing spatial-temporal data, with examples including climate patterns.checked 8 Oct 2026
- Interfaces
- The standard interface accepts NumPy or dask arrays, and metadata interfaces support Iris or xarray data.checked 8 Oct 2026
- Large datasets
- The package is designed to compute efficiently on large output datasets from modern climate models.checked 8 Oct 2026
- License
- The repository describes eofs as licensed under GNU GPLv3.checked 8 Oct 2026
- Metadata
- Metadata from input fields is used to construct metadata for output fields.checked 8 Oct 2026
- Missing values
- Missing values are removed during computations and placed back into output fields.checked 8 Oct 2026
- Purpose
- eofs is a Python package for empirical orthogonal function analysis of spatial-temporal data.checked 8 Oct 2026
- Regression models
- Nochecked 24 Sep 2026
- Requirements
- NumPy is required; Dask is optional, while the Iris interface requires Iris 1.2 or higher and the xarray interface requires xarray.checked 8 Oct 2026
- Research citation
- The documentation asks users of eofs in published research to cite its peer-reviewed paper.checked 8 Oct 2026
- Scripting support
- Yeschecked 24 Sep 2026
- Statistical tests
- Nochecked 24 Sep 2026
Money
- Free plan
- Yeschecked 24 Sep 2026
Where it runs
- Platforms
- The package runs on Linux, Windows, and MacOS where Python and NumPy are available.checked 8 Oct 2026
