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Getting Started

To participate in the hands-on tutorials and get started exploring the outputs of the NOC Near-Present Day simulations, we strongly recommend that participants use the one of the pre-prepared Python virtual environments which contain all of the required Python packages already.

Downloading Tutorials

Let's start by making a local copy of the NEMO_Cookbook_tutorial GitHub repository containing the Jupyter Notebooks used in the tutorial.

Navigate to your chosen working directory, and then clone the GitHub repo:

git clone https://github.com/promote-project/NEMO_cookbook_tutorial.git

Once the download is complete, you will see that a new NEMO_cookbook_tutorial directory has been added to your working directory.

Inside NEMO_cookbook_tutorial, you will find:

Note

Editing any of the tutorial or example notebooks / creating new notebooks in your cloned NEMO_cookbook_tutorial will not impact the original GitHub repository.

Configuring Jupyter Kernel

To get started running the tutorial notebooks, you need to set-up a Jupyter Kernel - the computational engine for your Python code.

We have already installed all of the necessary packages for the tutorial notebooks in two shared Conda environment accessible by everyone with terrafirma or canari group workspace access on JASMIN.

What is Conda?

Conda is a package manager which allows users to install software packages into dedicated virtual environments. This enables us to create different virtual environments, including different versions of the same software, for separate projects.

Virtual environments can also be shared between users by exporting them to a .yml file, which can be used to re-create the environment on another computer.

Conda is especially suited to scientific software applications since it can handle complex dependencies and pre-compiled binaries (e.g., netCDF4 to read netCDF files)

There are many different types of Conda package manager available:

  • Anaconda - Includes lots of common software, requires paid license.
  • Miniconda - Minimal version of Anaconda.
  • Miniforge - Minimal Conda package manager using only conda-forge (community) channel, exempt from licensing above.

To install a Jupyter kernel for the env_nemo shared Conda environment, run one of the following commands in your terminal:

CANARI GWS:

/gws/ssde/j25b/canari/public/env_nemo/bin/python -m ipykernel install --user --name env_nemo --display-name "PROMOTE Sprint (env_nemo)"

Terrafirma GWS:

/gws/ssde/j25b/terrafirma/otooth/env_nemo/bin/python -m ipykernel install --user --name env_nemo --display-name "PROMOTE Sprint (env_nemo)"

This will add a new Jupyter kernel called env_nemo to your kernelspec.

Now, when we open a Jupyter Notebook (e.g., tutorials/tutorial_0_getting_started_with_nemo_cookbook.ipynb), we will see a Select Kernel drop-down menu and included in the list is PROMOTE Sprint (env_nemo) kernel.