cf-training

Training material on the CF data tools cf-python and cf-plot.

These are practical materials used for NCAS training workshops, but they are self-contained and permanently available so are also suitable for outside (private) study (in which case see the Setup section below for guidance on setting up the required environment to run the software and the Notebooks).

The format of the courses is a series of Jupyter (formerly known as IPython) Notebooks.

Structure

There are two courses available:

• a full course (see the full_course directory) which contains all of the material for the full-day NCAS Data Tools training workshop. As a guide, it is designed to take around ~1-2 days of dedicated study to work through.

• a short course (see the short_course directory) which contains a condensed summary of the full course, focusing on demonstrating core functionality. It is designed to take one hour to work/walk through. There are also accompanying summary slides to describe the relevant background.

Prerequisites

Both libraries are Python-based but don't require any previous Python knowledge to use.

Setup

Environment setup

If you wish to work through these materials in your own time, you will need to set up the following to install cf-python and cf-plot and to run the Jupyter Notebooks on a machine of your choice:

1. Install cf-python and cf-plot with all dependencies: see the installation instructions here which covers the installation of both libraries. Note you will need some of the listed optional dependencies for certain parts of the course e.g. for the regridding component.
2. Install the Jupyter Notebook software if you do not have it already. There are instructions on how to do so on the Jupyter site.

Downloading and working through the course

When you have completed the above, copy this repository to your machine either by downloading the tarball from the GitHub User Interface or by running git clone, e.g:

$ git clone https://github.com/NCAS-CMS/cf-training.git

then navigate to the notebooks directory of the relevant course and start up the notebook server there, e.g:

$ cd full_course/notebooks/
$ jupyter notebook &

This will open a listing of the Notebooks available in the browser. You will be able to open & run the Notebooks at your own pace.

Course order

The recommended order in which to work through the full course Notebooks is as follows, where all paths given are relative to full_course/notebooks/:

	Topic	Format	Notebook name & location
1.	Introduction	Overview & walkthrough	introduction.ipynb
2.	Reading and manipulating data	Walkthrough	cf_python.ipynb
3.	Reading and manipulating data	Exercises	exercises/cf_python_exercise_*.ipynb [*=1-5]
4.	Contour plots	Walkthrough	contour_plots.ipynb
5.	Contour plots	Exercises	exercises/contour_exercise_*.ipynb [*=1-2]
6.	Regridding data	Walkthrough	cf-python_regridding.ipynb
7.	Regridding data	Exercises	exercises/regridding_exercise_*.ipynb [*=1-2]
8.	Vector and line plots	Walkthrough	vector_line_significance.ipynb
9.	Wrap up	Summary	wrap_up.ipynb

Model solutions to the exercises can be found under the model_answers/ directory but you are encouraged to find the solutions yourself before consulting these. As well as the walkthroughs, there is detailed documentation available to reference, found:

• here for cf-python; &
• here for cf-plot.