Software and Tools¶

Programming language¶

This course can be followed using the Julia programming language. Why Julia? Julia is a new language designed from scratch for fast scientific calculations, and has a large and growing ecosystem, especially for astronomy, visualisation, and data science. If you are familiar with Python, using Julia will be similar and in AST4310 we will use simple interfaces to the language. Read our guide to Julia when coming from Python.

Besides the programming language used to run code, jupyter notebooks have a text component using the Markdown language. It will be used extensively in your project reports, and you are encouraged to get more familiar with it. The Markdown cheatsheet is a good reference. Familiarity with LaTeX is also important, but mostly to write equations, which can be included in Markdown using LaTeX syntax.

JupyterHub¶

It may be possible to run Julia from JupyterHub at UiO. Check this page again later for updates.

Installing Julia and necessary packages¶

Julia is open source and available for most operative systems. It is already installed in the linux machines at the Institute, and it is possible to connect to this system remotely with Jupyter in your browser (see below for details). We recommend you use Jupyter lab or VSCode/VSCodium for interacting with Julia notebooks.

Start by installing Julia itself:

macOS or Linux laptopWindows laptopInstitute linux machines

Open a terminal and run:

curl -fsSL https://install.julialang.org | sh

Install juliaup from the Microsoft Store. This can also be installed from the terminal:

> winget install --name Julia --id 9NJNWW8PVKMN -e -s msstore

Julia is already installed in the Institute's linux machines, but its module needs to be loaded from the terminal:

$ module load julia

Then start julia in the terminal:

$ julia

This should start the Julia REPL, and you'll see a prompt with julia>. Press the ] key to enter the Julia package manager, and the prompt should change to something like (@v1.11) pkg>. Here, you will install several basic packages with the command:

(@v1.11) pkg> add CairoMakie Colors HDF5 IJulia Interpolations NumericalIntegration PhysicalConstants  Unitful

One of the packages above is IJulia, which will install Julia kernels for Jupyter. These should show when you restart Jupyter lab or Jupyter notebook. For VSCode or VSCodium, it is recommended you install the extensions Julia and Jupyter.

Running Julia remotely from the Institute¶

If you are using Julia from the Institute's linux machines, it is possible to connect remotely via the browser in your laptop.

Warning

This procedure is technically more difficult and prone to failure, so it is recommended for advanced terminal users only.

Setting up Julia at the Institute is very similar to the setup of Python. Start by setting up your Python environment following the documentation, and ensure that your py313 environment is loaded. Follow section 2 to start jupyter lab remotely. When you start Jupyter, you should see a Julia kernel when you start a new notebook.

To ssh to your machine of choice, it is recommended to configure your ssh keys and ssh agent to avoid having to enter your password several times. Adding a proxy to your ~/.ssh/config makes connecting even easier:

Host my_machine
    ForwardX11 yes
    ProxyJump username@login.astro.uio.no