yt Quickstart

The quickstart is a series of worked examples of how to use much of the functionality of yt. These are simple, short introductions to give you a taste of what the code can do and are not meant to be detailed walkthroughs.

There are two ways in which you can go through the quickstart: interactively and non-interactively. We recommend the interactive method, but if you’re pressed on time, you can non-interactively go through the linked pages below and view the worked examples.

To execute the quickstart interactively, you have a couple of options: 1) run the notebook from your own system or 2) run it from the url https://girder.hub.yt/#raft/5b5b4686323d12000122aa8a. Option 1 requires an existing installation of yt (see Getting and Installing yt), a copy of the yt source (which you may already have depending on your installation choice), and a download of the tutorial data-sets (total about 3 GB). If you know you are going to be a yt user and have the time to download the data-sets, option 1 is a good choice. However, if you’re only interested in getting a feel for yt and its capabilities, or you already have yt but don’t want to spend time downloading the data, go ahead to https://girder.hub.yt/#raft/5b5b4686323d12000122aa8a.

If you’re running the tutorial from your own system and you do not already have the yt repository, the easiest way to get the repository is to clone it using git:

git clone https://github.com/yt-project/yt

Now start the IPython notebook from within the repository (we presume you have yt and [jupyterlab](https://jupyterlab.readthedocs.io/en/latest/) installed):

cd yt/doc/source/quickstart
jupyter lab

This command will give you information about the notebook server and how to access it. You will basically just pick a password (for security reasons) and then redirect your web browser to point to the notebook server. Once you have done so, choose “Introduction” from the list of notebooks, which includes an introduction and information about how to download the sample data.

Warning

The pre-filled out notebooks are far less fun than running them yourselves! Check out the repo and give it a try.

Here are the notebooks, which have been filled in for inspection:

• Welcome to the yt quickstart!
• Starting Out and Loading Data
• Mesh Structure
• Examining Data in Regions
• Simple Visualizations of Data
• Data Objects and Time Series Data
• Derived Fields and Profiles
• A Brief Demo of Volume Rendering

Note

The notebooks use sample datasets that are available for download at https://yt-project.org/data. See Welcome to the yt quickstart! for more details.

Let us know if you would like to contribute other example notebooks, or have any suggestions for how these can be improved.