Machine Learning tools for Space Weather and Plasma Physics

License: LGPL-2.1

Language: Scala

Keywords: machine-learning, plasma-physics, scala, space-physics, space-weather


Build Status

Machine Learning tools for Space Weather and Plasma Physics

Image courtesy NASA

courtesy NASA

PlasmaML is a collection of data analysis and machine learning tools in the domain of space physics, more specifically in modelling of space plasmas & space weather prediction.

This is a multi-language project where the primary modelling is done in Scala while R is heavily leveraged for generating visualizations. The project depends on the DynaML scala machine learning library and uses model and optimization implementations in it as a starting point for extensive experiments in space physics simulations and space weather prediction.

Getting Started

PlasmaML is managed using the Simple Build Tool (sbt).



  1. Scala
  2. sbt
  3. R


After installing all the pre-requisites,

  1. Clone this project
  2. From the root directory type sbt, you should see the sbt prompt.
  3. At the sbt prompt, choose appropriate sub-project project omni
  4. Compile the sources compile
  5. Run the scala console console

Try an example program

scala>TestOmniNarmax("2004/11/09/08", "2004/11/11/09", "predict")

Project Statistics

Sourcerank 6
Repository Size 55.1 MB
Stars 5
Forks 0
Watchers 4
Open issues 0
Dependencies 0
Contributors 1
Tags 0
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Top Contributors See all

Mandar Chandorkar

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