Installing the Necessary Software
There are a number of software that are recommended for you to install to conduct research in astronomy. As you will see, this guide is mainly made for Mac users. If you are thinking of going into research in astronomy, I highly recommend you to get a Mac. Many astronomical software packages were developed for Unix, which the Mac OS is based on. Python, the main programming language astronomers use today, is notoriously hard to work on Windows, with library clashes, 32/64 bit versions incompatibility, and “ghost libraries” (installed libraries, but unable to be called). You would really want the machine to be the last of your obstacle to work—getting a Mac would solve a lot of your woes. That said, here are the key software that you should install.
Anaconda, Jupyter Notebook
Anaconda is a Python distribution that comes with the most useful libraries and packages pre-installed. Jupyter, the interface that we use for executing our scripts, is bundled along with the installation. Other important data science packages such as SciPy, Matplotlib, and pandas are installed in the Anaconda distribution—you can check out the full list here. This reduces the time needed to install packages, which allows you to get started on doing science immediately. The good news is that Anaconda works for both Macs and Windows, and Windows users can get started Python with relatively little issues.
Which version of python should we install?
Even after 8 years since Python 3 was created, there isn’t quite a unanimous decision to the question if one should stay in Python 2 or move to Python 3. There are many reasons why one would choose Python 2 over Python 3, and that is not the scope of this site. Essentially, Python 2 is getting phased out by 2020, and I recommend that you install Python 3 in your Anaconda installation to get started. There might be instances where you need Python 2—we will deal with that later. Anaconda makes it easy to switch between Python 2 and Python 3.
Once you’re done with the installation, you will be directed to the Anaconda Navigator:
The first item on the navigator is Jupyter. Click “launch” to see if the installation is working properly. If it is, the navigator will shut down you will be directed to the Notebook through an automated script in Terminal.
From here on, I recommend that you create a unique folder just for your Jupyter notebooks. You notice that when the navigator opens Jupyter for you, it starts in your account directory, which is not where you want to create your notebooks in. You can make a new directory by going to Terminal, and type the command line “mkdir astronomy”. Your folder hence will be at “../Users/[computer-name]/astronomy”. You can (and should) launch Jupyter from your Terminal when you’re in your unique astronomy folder. Use the command:
DS9 is an astronomical imaging and data visualisation software that almost all astronomers use. Most images that we take using research grade telescopes are in fits/fts image format, which not many generic image software support. DS9 has a huge arrays of functions that are helpful for amateur and professional astronomers alike. You can use DS9 to create basic RGB images (mostly for PR) or you can use it to check for the pixel count with the table analysis tool.
DS9’s UI is quite intuitive, and it only take a few moments to familiarise yourself with the functions available in this powerful application. You can configure the GUI of DS9 if you like too. The default displays are the coordinate display, panner, magnifier, horizontal and vertical graphs, button bar, and colour bar. You don’t need any additional installation for DS9 to work.
Atom is a text-editor that we use alongside with Jupyter Notebook for scripts that are better run without using an interactive environment. We use a text-editor as it highlights the syntax of our code, which makes it easier to read, edit, and debug. Atom recognises a host of programming languages, and is extremely easy to get started on