Metadata-Version: 1.2
Name: datafold
Version: 1.1.3
Summary: A package providing manifold parametrization in the Diffusion Maps framework and identification of dynamical systems in the Koopman operator view with the Extended Dynamic Mode Decomposition.
Home-page: https://datafold-dev.gitlab.io/datafold
Author: datafold development team
Author-email: daniel.lehmberg@hm.edu
License: MIT
Description: 
        The package provides:
        
        * (Extended-) Dynamic Mode Decomposition (EDMD) to approximate the Koopman operator for 
          system identification. 
        * Diffusion Maps to find meaningful geometric descriptions in point clouds, such as the 
          eigenfunctions of the Laplace-Beltrami operator. 
        * Data structure for time series collections (TSCDataFrame) and dedicated 
          transformations, such as time-delay embeddings (TSCTakensEmbedding). The data 
          structures operate with both EDMD and DMAP.  
        
Keywords: machine learning, dynamical system, data-driven, time series, time series regression, time series forecasting, manifold learning, koopman operator
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.7
