In this Jupyter Notebook we will use Python to explore and analyse some astronomical data. The techniques used here are (mostly) common to all sorts of 3-D datasets, however, we will be using some astronomy specific libraries to access astronomical data in FITS format.
We will create a Python 3 anaconda environment to ensure that everybody has the same modules and versions. Create the environment by executing the following on the command line:
conda env create -f astroEnv.yml
You will need to download some astronomical data-cubes to complete this exercise. Execute the following on the command line:
wget http://web.science.mq.edu.au/~cpurcell/public/downloads/dataHOPS.zip
Once everything is installed, activate the new conda environment and start the Jupyter Notebook:
source activate astroEnv
jupyter-notebook