Visualising HEALPix results with Jupyter Notebook

Tom Bradford Tom Bradford Mar 07, 2022 · 2 mins read
Visualising HEALPix results with Jupyter Notebook
Share this

In this tutorial we’ll be showing you how to visualise HEALPix results using Jupyter Notebook in our OnDemand appliance on the Apocrita HPC cluster. We’ll start with installing the required Python packages before demonstrating how to run the Healpy tutorial

Information about running other components of HEALPix not covered in this tutorial can be found on our docs site.


Using pip and virtualenv

The installation procedure follows the standard method for virtual environments on a shared system.

Virtual environments allow us to install different collections of Python packages without experiencing conflicts, or versioning issues.

Loading applications using the module command

Running module avail python will show the available Python versions; module load python without the version number will load the default version into the current session, and will also provide the pip and virtualenv commands. We’ll load the python/3.8.5 module to match the version of Python compatible with HEALPix.

module load python/3.8.5

Installing the Python packages in a virtual environment

We will now demonstrate how to create a virtual environment and install the healpy and ipykernel packages, using the following commands:

virtualenv ~/healpix
source ~/healpix/bin/activate
pip install healpy ipykernel

The above commands only need to be run once - the ~/healpix virtual environment will continue to exist until removed or renamed.

Activating virtual environments within Jupyter Notebook

By default, virtual environments are not available within Jupyter Notebook. To enable this functionality, simply run the following command with the virtual environment activated:

python -m ipykernel install --user --name healpix

You only need to run this command once. The virtual environment will remain available within Jupyter Notebook as long as it is present in the original install location.

A similar process for Anaconda is also documented here.

Running the tutorial

Starting a Jupyter Notebook session in OnDemand

Now if you open a new Jupyter Notebook (CPU) session from OnDemand, you will notice that the new healpix virtual environment is available under the Kernel -> Change Kernel menu, with the name healpix. Similarly, it will be available as an option under the File -> New notebook menu.

Let’s create a new notebook and use the healpix kernel. Save this file as healpy_tutorial.ipynb. Note that the currently active environment is displayed in the top right corner.

Now, enter the Python code as published in the tutorial:

Click Run to execute the notebook and produce the same output as published in the tutorial, shown below:

Exiting the Jupyter Notebook session

When you have finished your analysis on Jupyter Notebook, please remember to delete your job by clicking the red Delete button within the OnDemand appliance to return the requested resources to the cluster queues.

Tom Bradford
Written by Tom Bradford
Research Applications Team Leader. He likes football, cricket, gaming and KFC.