EnDAS¶
Ensemble Data Assimilation for Python 3.x.
Overview¶
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
Requirements¶
EnDAS is written in Python 3, using NumPy and SciPy. Therefore, if you cannot use either, EnDAS is unfortunately not for you. Apart from these, you will need a working C/C++ compiler for building some parts of EnDAS. See the Installation instructions page for more information.
Installation¶
For installation instruction see the Installation instructions page.
Documentation¶
TO BE COMPLETETED.
Code examples can be found in the examples directory of the EnDAS repository on GitHub.