SWATNET School 1: Introduction to Space Weather

A jupyter notebook designed for the AI Lecture 2 of the SWATNET School 1 in Novmember 2021 (https://swatnet.eu/school-1-introduction-to-space-weather/)  It will help you to get familiar with some basic coding skills to build a machine learning model to solve space weather problems using Support Vector Machines (SVM).

Download codes: https://github.com/PyDL/AI-Lecture2

ASDA - Automated Swirl Detection Algorithm

ASDA is a Python package for automated swirl detection using MPI programming.  We have done a series test using ASDA to detect swirls in a series of synthetic dataset, various numerical simulations, and both ground-based and space-borne observations.

Download codes: https://github.com/PyDL/ASDA

Pyflct - Python wrapper for FLCT

Pyflct is a Python wrapper for FLCT code written in C from Fisher & Welsch 2008. You can download the original C code from the following link: http://cgem.ssl.berkeley.edu/cgi-bin/cgem/FLCT/home

Before a proper run of this program, you need first install the FLCT libraries. Extract the downloaded C source files, go to the fold. Then check source/README-install.txt and Makefile to find out how to install the FLCT libraries properly.

Download codes: https://github.com/PyDL/pyflct

CAT-PUMA: CME Arrival Time Prediction Using MAchine learning algorithms

CAT-PUMA is a new tool allowing the community to perform CME arrival time predictions using machine learning algorithms. CAT-PUMA is fast - it gives predictions within minutes after users providing necessary parameters. CAT-PUMA is also accurate - it gives an average absolute prediction error of 5.9 hours on the CME arrival time at Earth. I have designed a user-friendly user interface (UI) with two examples for demonstrating how people can use CAT-PUMA to perform their own predictions.

Download codes: https://github.com/PyDL/cat-puma