A collection of science-driven tutorials for using the Pyleoclim Python package. Contributed by: Deborah Khider, Julien Emile-Geay, Alexander James, Feng Zhu, Jordan Landers, Pin-Tzu Lee

The notebooks folder contains Jupyter Notebooks that illustrate the main classes of the Pyleoclim user interface, using data hosted either in the Cloud or in the data directory.

The notebooks are organized in three levels:

• Level 0: basic tutorials to understand the main classes and their uses, requiring minimal knowledge of Python
• Level 1: more advanced tutorials involving customization and more knowledge of Python
• Level 2: tutorials involving more advanced data analysis techniques, requiring some domain knowledge to apply and interpret properly.

You may start by browsing this repository to consult its notebooks, which are rendered by the Github website. If you like what you see, we encourage you to experiment with them, as per the following section.

myBinder allows you to run the notebooks in a no-install cloud container. This is the best solution if you just want to get you feet wet with the code. Simply click on the "launch Binder" badge at the top of the page. The notebooks will be automatically pulled into your workspace. Beware: it takes a few minutes for the BinderHub to be spun up the first time around. After repeated uses (not just by you) it becomes much faster, but the first time you launch might need to coincide with a coffee break, a run around the nearest park, or catching up on the literature.

If it's love at first sight and you want to take Pyleoclim home with you, you may use the environment.yml file with conda to install the required packages within an anaconda or miniconda installation. That is, open a terminal, navigate to a folder containing environment.yml , then run the command :

conda env create -f environment.yml

This will install all the required packages and their dependencies. It may take a few minutes the first time, but after that you will have the power of Pyleoclim at your local disposal.

If you are new to conda, just know that it is an environment manager for Python. What is an environment, you may ask? Think of it as a piece on your computer where all the Python libraries that you need for a specific application live in perfect harmony. To access this paradise, you need to activate the environment. If you used the environment.yml file:

conda activate pyleo

Coming Soon (September 2022)

If you have access to a decent internet connection and do not want to install Python and Pyleoclim on your machine, you can also run these (and your own) notebooks on the LinkedEarth JupyterHub. To do so, please contact LinkedEarth to obtain an account, which may take 1-2 business days to review. Use of the LinkedEarth Hub implies that you subscribe to the LinkedEarth code of conduct which pretty much amounts to being a decent human being. This is a good solution if you intend on using Pyleoclim in your own work, particularly for paleoclimate data-model comparisons.

If you choose this route, know that the PyleoTutorials notebooks will not be directly pulled to the hub (unlike the myBinder solution). You will first need to download, clone or fork this repository onto your local machine. You can do so by clicking on the green 'code' button at the top (right above the list of files in the repository):

To learn more about cloning/forking, see this post. Downloading is just a one time action.

Once the notebooks and data are on your local machine, you can upload them to your private instance on the hub using this tutorial.

Please note that the notebooks use specific paths that you will either need to correct in the cells or reproduce on the hub (i.e., the notebooks and data folders).

Whichever path you choose, happy Pyleocliming, and please consider joining our user community on Discourse. It is the best place to provide feedback on any of this, and make requests for new tutorials.

This work was supported by NSF Grant ICER 2126510.