Notebook Conventions

Setup Pattern

All notebooks should start with the standard setup cell:

using Revise
using Linear_Algebra
using LAlatex, BlockArrays

LAlatex.set_backend!(:symbolics)
LAlatex.reset_display_defaults!()

using Linear_Algebra provides everything the module reexports, including LaTeXStrings (the L"..." macro). LAlatex and BlockArrays are notebooks-environment dependencies only (in notebooks/Project.toml, not the root project), so they need their own using line — they are not re-exported by the module. set_backend!(:symbolics) is required because this package uses Symbolics.jl; the default :latexify backend gives worse output for symbolic expressions. reset_display_defaults!() ensures a clean display state on every kernel restart.

Notebook Guidelines

• Notebooks are for exploration and study, not tested in CI

• The notebooks/ environment is not a workspace member — run pkg> dev .. + pkg> instantiate once after cloning. See julia-coding-conventions skill for the full pattern. Do not commit notebooks/Manifest.toml.

• Use println() for output to make results clear when re-running cells

• Include explanatory markdown cells between code cells

• Use Unicode variable names consistent with the source code (e.g., v₁, θ, λ)

• Reference the documentation sections being studied

Plotting in Notebooks

• Plots render inline in Jupyter notebooks

• No need for headless mode configuration

• Use the same plotting functions from the package (plot_param_line, etc.)

LAlatex Display

LAlatex.jl (by ea42gh) is available in the notebooks environment (using LAlatex in the setup cell) and provides clean LaTeX rendering of linear algebra objects in notebooks. Use it instead of raw println or display whenever presenting mathematical results.

Core functions

Common options for l_show

l_show(L"A = ", A; arraystyle=:bmatrix)          # bracket style: :bmatrix, :pmatrix, :vmatrix, :array
l_show(expr; symopts=(expand=true,))              # symbolic transformations: expand, factor, collect
l_show(A; number_formatter=x -> round_value(x,2)) # custom number formatting
l_show(A; number_formatter=percentage_formatter)  # percentage display
l_show(aligned(...); inline=false, tag="1")        # numbered display equation (no label — see below)
with_display_defaults(arraystyle=:bmatrix) do ... end  # scoped defaults

Block-partitioned matrices

Wrap a plain matrix in BlockArray to get visual partition lines (horizontal \hline and vertical | separators) between blocks:

B = BlockArray([1 2 4; 3 4 5], [1, 1], [2, 1])   # row sizes [1,1], col sizes [2,1]
display(l_show(L"B = ", B))

KaTeX constraint: no \label

Jupyter notebooks render math with KaTeX, which supports \tag{...} but not \label{...}. Never pass the label= keyword to l_show in a notebook — it will produce a parse error. Use tag= only:

# ✅ correct
display(l_show(aligned(...); inline=false, tag="1"))
# ❌ will fail in Jupyter
display(l_show(aligned(...); inline=false, tag="1", label="eq:foo"))

label= is only valid when rendering to full LaTeX/MathJax (e.g. Documenter.jl docs).

Reference

• LAlatex.jl docs

• Demo notebook (upstream)

• Interactive Binder demo

Julia Kernel Gotchas

See julia-coding-conventions skill (stale variable slot, building matrix from row vectors).