| File | What | When |
|---|---|---|
W04_lecture.html
(.qmd source) |
Lecture slides — Parts A, B, C, D | in class |
W04_lab.ipynb
(Colab) |
In-class lab: fem.Function in parallel, ways to
interpolate, polynomial preservation, errors and rates, three classic
mistakes, interpolation and I/O, LLM demo |
in class (≈ 80 min) |
W04_HW4.ipynb
(Colab) |
HW4 — 1D interpolation estimates and scaling, convergence study (smooth and singular functions, graded meshes), harmful triangle shapes, transfer between non-matching meshes with an LLM | due before Week 5 |
../dolfinx_0.11_api_reference.md |
DOLFINx 0.11 API reference sheet (updated §4: vectorised callables,
cells0=, non-matching interpolation) — paste it into your
LLM |
always |
Open a notebook in Colab: click its link on the
course page or below — it opens in Colab; then File → Save a copy in
Drive and work on that copy. (Or upload the .ipynb to
Google Drive → right-click → Open with → Google Colaboratory.)
Run the setup cell first (≈ 3–5 min); re-run it after every runtime
restart.
Where code can run: basix,
ufl and dolfinx exist only inside
%%fenicsx cells. Ordinary cells have NumPy and matplotlib
only. Output files (.bp, .xdmf) are written to
/tmp/fnx/; download them from the Colab file browser to
open them in ParaView.
Before submitting: Runtime → Restart session and
run all, fill in the AI-usage log, download the
.ipynb. An error inside a %%fenicsx cell does
not stop Run all: the traceback is printed and
the next cell runs anyway. Scroll through every output before you
submit. A cell that printed a traceback, and any plot that uses its
results, earns no points.
Week 5 starts with a 10-minute quiz on this week’s material (closed-AI).