Bokeh is a library to create interactive plots easily from a number of programming languages, including Python. The result is saved to an HTML page that can be viewed with any modern browser.

Note: out of the box, these notebooks work with Jupyter Notebook, not Jupyter Lab!

1. bokeh_intro.ipynb: Jupyter notebook showing some basic plotting capabilities of Bokeh.
2. function_plot.py: a simple script to plot multiple functions on the same figure.
3. HIVseries.csv: data set to use with viral_load.py.
4. ising.py: Visualizes the graphical solution to the equation of the magnetization of the 2D Ising model in the mean field approximation. The temperature (i.e., beta = 1/T) can be varied using a slider. Note: this is intended to be run using Bokeh server, see below.
5. pendulum.ipynb: Jupyter notebook illustrating interactive plots with widgets, linked plots and a hover tool.
6. viral_load.ipynb: Jupyter notebook to interactively adjust the parameters of a model for HIV viral load to fit experimental data.

To use ising.py, run it with the Bokeh server, i.e.,

$ bokeh serve  --show  ising.py