Metadata-Version: 2.1
Name: pyspod
Version: 0.4
Summary: Python Spectral Proper Orthogonal Decomposition
Home-page: https://github.com/mengaldo/PySPOD
Author: Gianmarco Mengaldo
Author-email: gianmarco.mengaldo@gmail.com
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: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Mathematics
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: xarray
Requires-Dist: netcdf4
Requires-Dist: h5py
Requires-Dist: psutil
Requires-Dist: tqdm
Requires-Dist: Sphinx
Requires-Dist: sphinx-rtd-theme
Requires-Dist: ecmwf-api-client
Requires-Dist: cdsapi
Requires-Dist: pyFFTW
Requires-Dist: future
Requires-Dist: ffmpeg
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  fluidmechanics applicaitons, and it can be used for both canonical problems  as well as large datasets. 


