This repository contains Jupyter notebooks written in Python that illustrate the use of ODEs in applications:
- Chaotic Dynamics: visualize chaotic attractors in the Lorenz and Rössler models
- Nonlinear pendulum: compute solutions to the nonlinear pendulum (mouse clicks define initial position and velocity) and animate them using a pendulum
- SIR model: visualizes solutions to SIR models and compares them with COVID-19 data
- Tipping points: provides interactive explorations of saddle-node bifurcations, tipping points, and hysteresis in models of budworm populations and global climate energy balances
- Yeast model: explores the logistic equations and fits its solutions to experimenbtal yeast growth data.
If you would like to run these notebooks in your webbrowser using Binder, click on the badge below. It may take time for Binder to start, and the notebooks may also run significantly slower than when ran locally.
Alternatively, install a JupyterLab with a Python 3 kernel locally using, for instance, Anaconda. If the command %matplotlib widget results in an error, replace it with %matplotlib notebook.