Creating Notebooks with CyberGIS
Using the Development Environment
Only Python 3 is currently supported by CyberGISX, though this may change in the future. Support for R is currently being developed. The CyberGISX environment has a number of available libraries that are ready for you to use, a list of which can be found here. It is possible to install your own libraries using “conda install -y lib” or “pip install -u lib==version” from a terminal launched in the notebook dashboard, though we request that you only do this if you know what you are doing and are comfortable with the coding environment.
You can upload data and other files from your home computer to the CyberGISX Jupyter environment. After that, you can access these resources from within your notebook. If the data you wish to use is large and may be of use to many users, contact us at email@example.com to inquire about storage on the shared data directory. The shared data directory is accessible at /home/jovyan/shared_data/
Accessing Computing Infrastructure
By default, each notebook server has access to 2 cores and 4GB of memory. We have a limit of 10G of data in your home directory. If you need more space to store your input data you may contact us at firstname.lastname@example.org. Additionally, datasets that would be of broad interest could be, upon request, stored in the shared directory.
It is possible to access High-Performance Computing resources in a notebook. You can access Keeling or other remote computers such as XSEDE’s Comet, however, certain restrictions apply. Contact us at email@example.com for more information.