kal-cal

Kalman Filter and Smoother RI Calibration

kal-cal is a Python library developed to provide proof-of-concept tools for Kalman Filtering and Smoothing Theory (see Bayesian Filtering and Smoothing by Simo S ̈arkk ̈a) as a replacement calibration framework for Radio-Interoferometric Gains Calibration (see Non-linear Kalman Filters for calibration in radio interferometry by Cyril Tasse). This library is part of the master's thesis work of Brian Welman (@brianWelman2 on github) through Radio Astronomy Techniques and Technologies under SARAO during the period of 2020 to 2021.

Requirements

The only external requirement is the casa command from casalite. Otherwise, all Python packages are listed in requirements.txt.

Installation

Firstly, you need at least python3, or even better python3.6.9, as this is the version the library was developed on. Use the package manager pip to install kal-cal as follows:

pip install https://github.com/brianwelman2/kal-cal/archive/refs/heads/main.zip

Usage

To import kal-cal:

import kalcal

Documentation

TBD

CI

This library uses github-actions for continuous integration tests on the same repository.

License

This package uses the MIT license.