Notebook Tutorials and Demonstrations

This is a collection of tutorial notebooks and demonstrations for the self-driving-lab-demo! First, you should get started with the main, public-facing tutorial. Just click the following “Open in Colab” badge: Open InColab

All Tutorials


Tutorials from sections 1, 2, and 3 are deprecated due to changes in hardware and software design of the demo (i.e., dropping “Blinkt!” in favor of built-in RGB LED on Maker Pi Pico base, and dropping a web server interface in favor of MQTT). Since they are instructive and show parts of the behind-the-scenes development process, they are kept here for reference and provenance.

1. Blinkt! Getting Started (deprecated)

2. Search Algorithms using Blinkt! (deprecated)

3. Pico W with a Web Server (deprecated)

IoT-style control of Pico W

Wired control of Pico W

Advanced optimization

Data ecosystem

eScience 2022

See also a set of tutorials prepared for the eScience 2022 conference. Video tutorials corresponding to these notebooks are published on YouTube in Taylor Sparks’ Optimization playlist.

More to come!

  • discrete multi-fidelity optimization (simulation and experiments)

  • high-dimensional Bayesian optimization (SAASBO, MORBO)

  • scalable Bayesian optimization (MORBO, Dragonfly)

  • asynchronous/batch optimization using network of experiments

  • Grid search vs. random vs. Sobol vs. stochastic gradient descent vs. genetic algorithm vs. Bayesian optimization (e.g. via Olympus benchmarking platform)

  • Repeat experiments for high-variance or failure-prone experiments via RayTune Repeater

  • Combinations of above

  • External evaluation of simulation functions (e.g. FuncX, Slurm, AWS, Google Cloud)

  • Experimental orchestration software via Bluesky

  • Storing experiments in a database backend (e.g. SQL, MongoDB)

  • Combinations of above

Any requests? Post on the issue tracker 😉