¡AnDA! is a Python library for the Analog Data Assimilation. This fully data-driven approach aims at reconstructing the state of the system without knowing explicitly the dynamical model. Instead, a representative catalog of trajectories of the system is assumed to be available. AnDA combines analog forecasting methods with ensemble data assimilation.
A description and a test of the code is given in the ipython notebook "test_AnDA.ipynb".
Please contact Pierre Tandeo (pierre.tandeo@imt-atlantique.fr) in case of bugs.
The Matlab code is also available on demand but will not be supported for the future. We advice new users to consider using the AnDA Python library which does not need special Matlab toolbox licences and is used by the authors in their future works.
This Python library is attached to the following publication (http://journals.ametsoc.org/doi/abs/10.1175/MWR-D-16-0441.1): Lguensat, R., Tandeo, P., Ailliot, P., Pulido, M., & Fablet, R. (2017). The Analog Data Assimilation. Monthly Weather Review, 145(10), 4093-4107. If you use this library, please do not forget to cite our work.
Copyright © 2019 Pierre Tandeo pierre.tandeo@imt-atlantique.fr.
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License version 3 as published by the Free Software Foundation. See LICENCE file.