Metadata-Version: 2.1
Name: pyspod
Version: 1.0.0
Summary: Python Spectral Proper Orthogonal Decomposition
Home-page: https://github.com/mengaldo/PySPOD
Author: Gianmarco Mengaldo, Romit Maulik, Andrea Lario
Author-email: mpegim@nus.edu.sg, rmaulik@anl.gov, alario@sissa.it
License: MIT
Keywords: spectral-proper-orthogonal-decomposition spod
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Mathematics
License-File: LICENSE.rst
Requires-Dist: numpy
Requires-Dist: psutil
Requires-Dist: scipy
Requires-Dist: tensorflow
Requires-Dist: Sphinx
Requires-Dist: xarray
Requires-Dist: cdsapi
Requires-Dist: opt-einsum
Requires-Dist: tqdm
Requires-Dist: sphinx-rtd-theme
Requires-Dist: h5py
Requires-Dist: matplotlib
Requires-Dist: netcdf4
Requires-Dist: ecmwf-api-client
Requires-Dist: future
Requires-Dist: pytest
Provides-Extra: docs
Requires-Dist: Sphinx (==3.2.1) ; extra == 'docs'
Requires-Dist: sphinx-rtd-theme ; extra == 'docs'

PySPOD is a Python package that implements the Spectral Proper Orthogonal Decomposition (SPOD). SPOD is used to extract perfectly coherent spatio-temporal patterns in complex datasets. Original work on this technique dates back to (Lumley 1970), with recent development brought forward by (Towne et al. 2017), (Schmidt et al. 2018), (Schmidt et al. 2019).

PySPOD comes with a set of tutorials spanning weather and climate, seismic and  fluid mechanics applications, and it can be used for both canonical problems  as well as large datasets. 


