UC Berkeley PhD Thesis

This is the repository for my thesis. If you'd just like to read the paper, feel free.

This repository is laid out in a manner described in Good Enough Practices in Scientific Computing.

The content itself has been broken into a few standalone papers and uploaded to the arXiv and / or submitted to journals:

• K-Compensated de Casteljau paper (GitHub repo, submitted to AMC)
• 2-Norm Condition Number for Bézier Curve Intersection (GitHub repo)
• A Curious Case of Curbed Condition (GitHub repo)
• High-order Solution Transfer between Curved Meshes (GitHub repo); yet to be released / submitted

In addition, this repository has slides for:

• Thesis talk

Installation

The code used to build the manuscript, generate images and verify computations is written in Python. To run the code, Python 3.6 should be installed, along with nox-automation:

python -m pip install --upgrade nox-automation

Once installed, the various build jobs can be listed. For example:

$ nox --list-sessions
Available sessions:
* build_tex
* make_images
* update_requirements

To run nox -s build_tex (i.e. to build the PDFs), pdflatex, xelatex and bibtex are required. In addition the metropolis Beamer theme should be installed, as well as the Fira font family.