Clustering Geo-data Cubes (CGC) Tutorial

This repository contains notebooks that illustrate how to use CGC, a clustering tool for geo-spatial data. The code is hosted on GitHub, and its full documentation is available here.

You can run this tutorial in a live JupyterLab session on mybinder.org by clicking on the following badge:

Notebooks

Installation

Clone this repository and access its root directory:

git clone http://github.com/esciencecenter-digital-skills/tutorial-cgc.git
cd tutorial-cgc/

In order to run the notebooks, you will need:

• Python 3.8, 3.9 or 3.10;
• Having the following packages installed:
  • CGC (and its dependencies)
  • Xarray and Zarr to read the example data set (requests and aiohttp enable accessing the data set from the web)
  • Jupyter

This repository includes a configuration file (environment.yml) that allows you to install CGC, Xarray and Zarr using conda:

conda env create -f environment.yml

Activate the cgc-tutorial environment:

conda activate cgc-tutorial

Install Jupyter

Jupyter can be installed using pip:

pip install jupyter

The official Jupyter documentation can be found here.

Running the Notebooks

From the repository notebooks directory, run:

jupyter notebook