Pynbody Tutorials

Here you will find tutorials that illustrate the use of pynbody. The Walkthroughs demonstrate pynbody functionality through an interactive session in the ipython shell that you can follow along using either one of the outputs from the bundled test-data or one of your own simulations. To complement the walkthroughs, we also provide a quick-start Jupyter notebook. The Cookbook/Recipes tutorials are more goal-oriented: they provide a script that can be used with only minor modifications to immediately produce a result (i.e. make an image). They also include, however, a somewhat more involved discussion of more advanced options and common pitfalls. Finally, the Advanced topics section is meant to provide a more in-depth look at the inner-workings of the code.

Obtaining test data

Many of the tutorials below use the same dataset that pynbody is tested on. While they are easily adapted for your own data, you can also download and unpack the test data to replicate the examples exactly. To do this, perform the following steps:

1. Download the testdata tarball from here. This is approximately 2.0GB. From a command line, you can do this with the command

   $ wget http://star.ucl.ac.uk/~app/testdata.tar.gz
   

2. Unpack the tarball in a directory of your choice. This will create a directory called testdata.

   $ tar -xzf testdata.tar.gz
   

3. Launch python, ipython or jupyter from the directory where you unpacked the tarball. You can then follow the tutorials below, using the testdata directory as the root of your data.

Walkthroughs

• Quick-start
• Reading snapshots
• Sub-views & filters
• Halos & groups
• Linking snapshots

Cookbook/Recipes

• Profiles
• Images
• Halo mass function

Advanced topics

These tutorials are likely to be of interest only in special cases.

• Performance
• Derived quantities
• Configuration
• Threading/multiprocessing