eahussein / dc1

This tutorial is based on the SKA Data Challenge 1. The aim of the tutorial is to learn to identify and classify sources is radio images. The data provided is simulated, to represent what the SKA data will look like once the telescope is in operation.
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classification machine-learning python radio-astronomy ska source-finding

DOI

The aim of the tutorials is as follows:

Data

3 different simulated data are used in this workflow, where the simulation represents the following frequencies:

>  bash binder/download_sample_data.sh

Hackathon Task

From the proposed pipeline, investigate new ways to find/classify sources.

Prerequisites

All the libraries/dependencies necessary to run the tutorials are listed in the requirements.txt file.

Installation

All the required libraries can be installed using pip and the requirements.txt file in the repo:

> pip install -r requirements.txt

Would you like to clone this repository? Feel free!

> git clone https://github.com/Hack4Dev/dataChallenge_hack.git

Then make sure you have the right Python libraries for the tutorials.

New to Github?

The easiest way to get all of the lecture and tutorial material is to clone this repository. To do this you need git installed on your laptop. If you're working on Linux you can install git using apt-get (you might need to use sudo):

apt install git

You can then clone the repository by typing:

git clone https://github.com/Hack4Dev/dataChallenge_hack.git

To update your clone if changes are made, use:

cd dataChallenge_hack/
git pull