pyassim 0.0.1

Package for data assimilation

# Data Assimilation repository
- this repository is under development

## How to Import
- `python setup.py install`
- this package requires `numpy`

## How to Test
- `python setup.py test`

## How to Use
- please see the codes under `samples/`
    - `sample_dom.py` is an example w.r.t. KF and LOCK through a twin experiment of dample oscillation model.
    - `sample_advection.py` is an example w.r.t. LLOCK, SLOCK, and LSLOCK through a twin experiment of advection equation.
    - `sample_Lorenz.py` is an example w.r.t. EnKF, NEnKF, PF, and GPF through a twin experiment of Lorenz 63 model.
- this repository includes following methods
    - [x] Kalman Filter (KF)
    - [x] Ensemble KF (EnKF)
    - [x] Nonlinear Ensemble KF (NEnKF)
    - [x] Local Ensemble Transform KF (LETKF)
    - [x] Linear Opeartor Construction with the Kalman Filter (LOCK)
    - [x] Local LOCK (LLOCK)
    - [x] Spatially Uniform LOCK (SLOCK)
    - [x] Locally and Spatially Uniform LOCK (LSLOCK)
    - [x] Bayesian LOCK (BLOCK)
    - [x] Local BLOCK (LBLOCK)
    - [x] Locally and Spatially Uniform BLOCK (LSBLOCK)
    - [x] Particle Filter (PF)
    - [x] Gaussian PF (GPF)
    - [x] Variational Mapping PF (VMPF)
    - [x] Hidden Markov Model (HMM)
- if you tackle high-dimensional problems, this repository provides following methods for memory efficiency
    - [x] Kalman Filter (KF)
    - [x] Local LOCK (LLOCK)
    - [x] Spatially Uniform LOCK (SLOCK)
    - [x] Locally and Spatially Uniform LOCK (LSLOCK)
    - [ ] Local BLOCK (LBLOCK)
    - [ ] Locally and Spatially Uniform BLOCK (LSBLOCK)
- checked items are already developed, the others are under development