Ensemble Data Assimilation for Python 3.x.
EnDAS is a data assimilation library for Python that focuses on ensemble data assimilation algorithms (although few others are also included for comparison). The main features are:
- Ensemble Kalman Filters and Smoothers including
- Traditional/stochastic EnKF
- Square root EnKF
- Ensemble Transform Kalman Filters
- Variational Ensemble Kalman Filter (still experimental)
- Traditional Kalman Filter and Smoother
- Distance-based localization of the analysis update, including few popular covariance tapering functions
- Non-intrusive filtering (and smoothing) API
- Utilities for generating random fields
EnDAS is written in Python 3, using NumPy and SciPy. Therefore, if you cannot use either, EnDAS is unfortunately not for you. Some parts of EnDAS are implemented as C/C++ extensions (using Cython) so you will need working C/C++ compiler and, if building from the GitHub source, Cython installed. EnDAS will work on any Python interpreter implementation compatible with the Cython such as CPython or PyPy. For more information see the installation instructions.
Documentation can be found at https://endas.readthedocs.io/en/latest.
Code examples can be found in the examples directory of the EnDAS repository on GitHub:
https://github.com/martingu11/endas.
For installation instruction see this page.