These are lecture notes for Computer Science 132, Geometric Algorithms, as taught by me at Boston University. The overall structure of the course is based on Linear Algebra and its Applications, by David C. Lay, Addison-Wesley (Pearson).
The notes are in the form of Jupyter notebooks. Demos and most figures are included as executable Python code. Lecture notes are also available in pdf, as converted using nbconvert.
The rationale for the teaching approach used in this course is here.
A separate set of questions, used for in-class peer instruction with clickers or TopHat, is available on request.
Course Versions
- Spring 2020 - current version. Updated to support diagram presentation via DiagramAR (https://apps.apple.com/us/app/diagramar/id1484987191).
- Fall 2015 - This semester the materials were converted to Python 3.4 and the 5th edition of the text. This set is available as the "Fall 2015 Final" release.
- Spring 2015 (4th edition of text, Python 2.7 code) - available as the "spring15-final" release
Software Used
Each workbook can be presented as a slideshow in Jupyter notebook using the RISE package, by @damianavila. This is how I give the lectures, typically modifying the code during the lecture to illustrate points or explore ideas that come up.
I use some notebook extensions to neaten and simplify the notebooks. For the best presentation experience, enable the "RISE," "Hide input," "Load TeX macros," and "split cells" extensions.
Most 3D diagrams in the notes can be viewed in augmented reality via the iPhone app DiagramAR. The app loads figures using the QR codes in the notes. The DiagramAR team includes Dennis Henneman (principal developer), Xiqiao Chen (designer), and Mark Crovella (project lead).