Optimization of Runge-Kutta time-stepping schemes with forward-backward averaging

Author: Jeremy Lilly

This repo contains Jupyter notebooks written in Python for obtaining "optimal" time-stepping schemes for the shallow-water equations (SWEs).

First-time setup

It is suggested to run these notebooks from within a virtual python environment (venv) rather than messing with the primary Python installation on your machine. To create a new venv:

python3 -m venv <path-to-new-venv>

For example, python3 -m $HOME/my-venv will create a new virtual python environment called my-venv in your home directory.

Next, activate the new venv and install the required packages with pip:

source <path-to-new-venv>/bin/activate
pip install -r requirements.txt

You can then leave the venv with:

deactivate

Usage

To run these notebooks after the above first-time setup, simply activate the venv:

source <path-to-new-venv>/bin/activate

Open the Jupyter notebook interface:

jupyter notebook

Then, use the GUI to navigate to and run the notebooks.

To shutdown the notebook server, simply hit CTRL-C in the terminal where the server was launched and follow the prompts. To leave the venv, run:

deactivate