diff --git a/.github/workflows/compile.yml b/.github/workflows/compile.yml new file mode 100644 index 0000000..8dfcc6e --- /dev/null +++ b/.github/workflows/compile.yml @@ -0,0 +1,33 @@ +name: Compile + +on: + push: + branches: + - main + paths: + - "src/**.typ" + +jobs: + render-paper: + runs-on: ubuntu-latest + permissions: + contents: write + steps: + - uses: actions/checkout@v4 + - uses: typst-community/setup-typst@v3 + with: + cache-dependency-path: requirements.typ + - name: Install fonts + run: sudo apt install -y fonts-noto + - name: Get current date + id: date + run: echo "date=$(date +'slides-%Y-%m-%d-%H-%M-%S')" >> $GITHUB_OUTPUT + - name: Compile + run: typst compile --font-path src/fonts/ src/main.typ ${{ steps.date.outputs.date }}.pdf + - name: Upload release + uses: softprops/action-gh-release@v1 + with: + files: ${{ steps.date.outputs.date }}.pdf + name: ${{ steps.date.outputs.date }} + tag_name: ${{ steps.date.outputs.date }} + diff --git a/Manifest.toml 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"1.4.1+1" diff --git a/Project.toml b/Project.toml new file mode 100644 index 0000000..e034574 --- /dev/null +++ b/Project.toml @@ -0,0 +1,6 @@ +[deps] +BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf" +ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210" +Latexify = "23fbe1c1-3f47-55db-b15f-69d7ec21a316" +Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80" +Symbolics = "0c5d862f-8b57-4792-8d23-62f2024744c7" diff --git a/README.md b/README.md new file mode 100644 index 0000000..2856be3 --- /dev/null +++ b/README.md @@ -0,0 +1,23 @@ +# An informal introduction to Julia + +Download the slides from [the latest release](https://github.com/astro-group-bristol/julia-intro/releases/latest). + +To setup Julia, install from [Julia Homepage](https://julialang.org/downloads/), or with your distribution package manager of choice. + +To gather all dependencies to run the examples, in the root directory start Julia: +```bash +$ julia -q +julia> + +# hit the `]` key +julia>] + +(@v1.10)> activate . +(julia-intro)> instantiate +``` + +This will grab all of the dependencies from the `Project.toml` (with the specific versions locked in the `Manifest.toml`). + +--- + +Montserrat font by [Julieta Ulanovsky](https://github.com/JulietaUla/Montserrat), licensed under SIL OFL. diff --git a/examples/01-trapezoid-julia.jl b/examples/01-trapezoid-julia.jl new file mode 100644 index 0000000..5a42229 --- /dev/null +++ b/examples/01-trapezoid-julia.jl @@ -0,0 +1,27 @@ +""" + integrate(f, x₁, x₂; N = 10_000_000) + +A magical integrator that integrates any function! + +Give it a box, and a function, and after a bit of time, out pops the area. +""" +function integrate(f, x₁, x₂; N = 10_000_000) + Δx = (x₂ - x₁) / N + + area = 0.0 + for i in 1:N + low = x₁ + (i - 1) * Δx + high = x₁ + i * Δx + area += Δx * (f(high) + f(low)) / 2 + end + + return area +end + + +quarter_circle(x) = √(1 - x^2) + +area = @time integrate(quarter_circle, 0.0, 1.0) ; + +println("π = $(Float64(π))\nEstimate = $(4 * area)") + diff --git a/examples/01-trapezoid-python.py b/examples/01-trapezoid-python.py new file mode 100644 index 0000000..8be9c00 --- /dev/null +++ b/examples/01-trapezoid-python.py @@ -0,0 +1,27 @@ +import math +import timeit + +def integrate(f, x1, x2, num_points = 10_000_000): + """ + A magical integrator that integrates any function! + + Give it a box, and a function, and after a bit of time, out pops the area. + """ + dx = (x2 - x1) / num_points + + area = 0.0 + for i in range(num_points): + low = x1 + i * dx + high = x1 + (i + 1) * dx + area += dx * (f(high) + f(low)) / 2 + + return area + +def quarter_circle(x): return math.sqrt(1 - x**2) + +start = timeit.default_timer() +area = integrate(quarter_circle, 0, 1) +duration = timeit.default_timer() - start + +print(f"Pi = {math.pi:.30}\nEstimate = {4 * area:.30}\n\nSeconds: {duration:E}") + diff --git a/examples/02-threaded-julia.jl b/examples/02-threaded-julia.jl new file mode 100644 index 0000000..478ba05 --- /dev/null +++ b/examples/02-threaded-julia.jl @@ -0,0 +1,65 @@ +using Plots + +# I have this function +f(x, a, b) = (x - ((b * x - 5sin(a))^2 )) / (2 + sin((b * x + 1) - 7a)) + 20 + +# It looks like this +xs = range(-5, 10, 200) +begin + p = plot() + for a in 1:3 + plot!(xs, f.(xs, a, 1), label = "a=$a") + end + hline!(p, [0], label = nothing, color = :black) + p +end + +function integrate_f(x₁, x₂, a, b) + integrate(x -> f(x, a, b), x₁, x₂; N = 100_000) +end + +# I want to know how the area changes as a function of the different +# parameters. So I add a dispatch that specializes when `a` is a vector. +function integrate_f(x₁, x₂, a::Vector, b) + areas = zeros(length(a)) + for i in eachindex(a) + aᵢ = a[i] + areas[i] = integrate_f(x₁, x₂, aᵢ, b) + end + areas +end + +# Lets see how the area changes when I change `a` +as = collect(range(-5.0, 3.0, 100)) +areas = @time integrate_f(-5, 10, as, 1) ; +plot(as, areas) + +# The curve changes rapidly, so it's good we can evaluate it fast because we +# need high resolution to see all the detail +# But I *actually* have two parameters I am interested in... +function integrate_f(x₁, x₂, a::Vector, b::Vector) + areas = zeros(length(a), length(b)) + Threads.@threads for i in eachindex(a) + aᵢ = a[i] + for j in eachindex(b) + bᵢ = b[j] + areas[i, j] = integrate_f(x₁, x₂, aᵢ, bᵢ) + end + end + areas +end + +# The problem I now have is that my parameters space has increased by two +# orders of magnitude, which means I would have to reduce resolution to see the +# result, but then I might miss something! + +# Fortunately, with Julia I can use the `Threads.@threads` macro to trivially +# multi-thread this (go up and add `Threads.@threads` before the first `for` +# loop and measure the speed increase! +bs = collect(range(-1, 1.0, 100)) +areas = @time integrate_f(-5, 10, as, bs) ; + +# Lets see our result! +heatmap(bs, as, areas, xlabel = "b", ylabel = "a") +contour!(bs, as, areas, color = :black) + diff --git a/examples/03-root-finding.jl b/examples/03-root-finding.jl new file mode 100644 index 0000000..80c575d --- /dev/null +++ b/examples/03-root-finding.jl @@ -0,0 +1,68 @@ +using Plots +using ForwardDiff + +function newton_root(f, x₀; N = 10) + df(x) = ForwardDiff.derivative(f, x) + for i in 1:N + x₀ -= f(x₀) / df(x₀) + end + return x₀ +end + +# Define a utility operator +∂(f) = x -> ForwardDiff.derivative(f, x) + +# A test function +g(x) = -(x - 1.2)^2 * cos(5x - 1) + 3 + +# Visualise it +xs = range(-1, 1, 100) +plot(xs, g) + +# Trivially plot the derivative +plot!(xs, ∂(g)) +hline!([0], linestyle = :dash, color = :black) + +# Our guess / starting point +# (please don't program with emojis) +🤔 = 0.0 + +# Solve for the root +🤠 = newton_root(∂(g), 🤔) + +# Plot the point +scatter!([🤠], [g(🤠)]) + +# But there's a few more! Add more guesses +x₀ = [-0.5, 0.5] +sols = newton_root.(∂(g), x₀) +scatter!(sols, g.(sols)) + + +# AD is *magical*, because we it treats the function as "opaque" It isn't doing +# symbolic things, so we can even take the derivative of our area integrals and +# solve for optimal points + +as = collect(range(-5.0, 3.0, 100)) +areas = @time integrate_f(-5, 10, as, 1) ; +plot(as, areas) + +# Define my derivative function +∂fa = ∂(a -> integrate_f(-5, 10, a, 1)) + +# Calculate and plot +deriv = @time ∂fa.(as) +plot!(as, deriv) + +# Think about what just happened there: our trapezoid integration function was +# called 100 times, but now propagating the `ForwardDiff.Dual` number type to +# let us find how the area changes as a function of `a`! Doing this with finite +# difference or stenciling methods would have been horrendous, but with Julia +# we can skip that and move on with our analysis. + +# Guess a ≈ -2 for the minima +a₀ = newton_root(∂fa, -2.0) + +# And plot the point +scatter!([a₀], [integrate_f(-5, 10, a₀, 1)]) + diff --git a/src/figs/auto-diff-youtube.png b/src/figs/auto-diff-youtube.png new file mode 100644 index 0000000..7abec51 Binary files /dev/null and b/src/figs/auto-diff-youtube.png differ diff --git a/src/figs/julia-source-to-native.png b/src/figs/julia-source-to-native.png new file mode 100644 index 0000000..cee9d70 Binary files /dev/null and b/src/figs/julia-source-to-native.png differ diff --git a/src/figs/julia_logo.svg b/src/figs/julia_logo.svg new file mode 100644 index 0000000..c608baf --- /dev/null +++ b/src/figs/julia_logo.svg @@ -0,0 +1,10 @@ + + + + + + + + + + diff --git a/src/fonts/MontserratBlack-3zOvZ.ttf b/src/fonts/MontserratBlack-3zOvZ.ttf new file mode 100644 index 0000000..91b91a9 Binary files /dev/null and b/src/fonts/MontserratBlack-3zOvZ.ttf differ diff --git a/src/fonts/MontserratBlackItalic-x3728.otf b/src/fonts/MontserratBlackItalic-x3728.otf new file mode 100644 index 0000000..586f9c3 Binary files /dev/null and b/src/fonts/MontserratBlackItalic-x3728.otf differ diff --git a/src/fonts/MontserratBold-p781R.otf b/src/fonts/MontserratBold-p781R.otf new file mode 100644 index 0000000..646985e Binary files /dev/null and b/src/fonts/MontserratBold-p781R.otf differ diff --git a/src/fonts/MontserratBoldItalic-ALPax.otf b/src/fonts/MontserratBoldItalic-ALPax.otf new file mode 100644 index 0000000..ae7ece1 Binary files /dev/null and b/src/fonts/MontserratBoldItalic-ALPax.otf differ diff --git a/src/fonts/MontserratItalic-5187x.otf b/src/fonts/MontserratItalic-5187x.otf new file mode 100644 index 0000000..f03a5ee Binary files /dev/null and b/src/fonts/MontserratItalic-5187x.otf differ diff --git a/src/fonts/MontserratRegular-RpK6l.otf b/src/fonts/MontserratRegular-RpK6l.otf new file mode 100644 index 0000000..1c53d67 Binary files /dev/null and b/src/fonts/MontserratRegular-RpK6l.otf differ diff --git a/src/main.typ b/src/main.typ new file mode 100644 index 0000000..8b2ab97 --- /dev/null +++ b/src/main.typ @@ -0,0 +1,497 @@ +#import "@preview/polylux:0.3.1": * +#import "tamburlaine.typ": * +#import emoji + +#show: tamburlaine-theme.with(aspect-ratio: "4-3") +#show link: item => underline(text(blue)[#item]) + +#enable-handout-mode(false) + +#let pretty-title = par(leading: 28pt)[ + #text(weight: "black", size:103pt, juliafy( + "An informal introduction to") + ) + #h(16em) + #move( + dx: -4em, + dy: -4.8em, + image("figs/julia_logo.svg", width: 40%) + ) +] + +#let fat-text(t) = { + text(size: 40pt, weight: "black", juliafy(t)) +} +#let boxed(t, fill-color: JULIA_RED) = { + rect(width: 100%, inset: (top: 10pt, bottom: 10pt), fill: fill-color, radius: 5pt, text(fill: SECONDARY_COLOR, t)) +} + +#title-slide( + title: pretty-title, + authors: ("Fergus Baker",), + where: juliafy("Astro Dev Group"), + date: datetime(year: 2024, month: 4, day: 26) +) + + +#slide(title:"Before we begin ...")[ + If you want to follow along: + - #link("https://julialang.org/downloads/")[https://julialang.org/downloads/] + - "One-liner" install + #v(-2em) + #align(right, fat-text("... alternatively ...")) + #v(-1em) + #block(inset: (left: 4em))[ + Julia is installed on the *Astrophysics Servers* + ] + #v(-1em) + #fat-text("Shell in, join in!") + #v(-0.5em) + #align(center, text(size: 14pt)[ + ``` + lx21966@hm00: ~ $ module load julia/1.8.5 + lx21966@hm00: ~ $ julia + _ + _ _ _(_)_ | Documentation: https://docs.julialang.org + (_) | (_) (_) | + _ _ _| |_ __ _ | Type "?" for help, "]?" for Pkg help. + | | | | | | |/ _` | | + | | |_| | | | (_| | | Version 1.8.5 (2023-01-08) + _/ |\__'_|_|_|\__'_| | Official https://julialang.org/ release + |__/ | + + julia> + ``` + ]) +] + +#slide(title:"Why Julia when there's X Y Z?", title-size: 42pt)[ + #v(-0.8em) + #boxed(fill-color: white.darken(10%), align(center, fat-text("The \"Two Language Problem\""))) + #v(-0.8em) + #grid( + columns: (50%, 50%), + [ + *Prototype* + - For _ease_ 😎 + - Simple language, quick to put stuff together 🔨 + - _Convenient_, few lines of code 🌝 + - Has all the tooling and utilities, nice package management 🥦 + ], + [*The real thing* + - For _speed_ ⚡ + - Complex language, time-consuming + - _Difficult_ and error prone 🪲 + - Many lines of code + - Probably won't do your analysis in this language 👀 + ] + ) + #boxed(fill-color: JULIA_GREEN)[ + Especially in *science*: skill disconnect between *researcher* and *developer* + ] + // - scalability + // - "plant once harvest forever" thanks to multiple dispatch +] + +#slide(title:"Solving the problem")[ + A language that does both! + - Julia is #text(fill: JULIA_RED)[*simple*], #text(fill: JULIA_PURPLE)[*fast*], and #text(fill: JULIA_GREEN)[*scalable*] + - Dynamically typed (optionally strongly typed) + - Lets you reach under the hood *when you need to* + #v(-1.0em) + #align(right, fat-text("And solve many more")) + #v(0.2em) + - Macro system for *domain specific languages* (DSLs) + - Multiple-dispatch for *highly optimized* execution / native and xPU backends / distributed + #v(-0.5em) + #boxed(fill-color: white.darken(10%), text(fill:TEXT_COLOR)[ + Julia is a *JIT* compiled, *garbage collected* language (MIT) + - *Compiler embedded* in the runtime, built on *LLVM* + - Lisp-style macros that manipulate AST + - C/Fortran ABI and *Python* interop (*! astro*) + ]) +] + +#slide(title:"Syntax")[ + #grid( + columns: (60%, 40%), + row-gutter: 10pt, + [ + ```julia + println("Hello World") + 5 + 3 + ``` + ```julia + items = [1, 2, 3, 4, 5, 6] + items[1] # indices start at 1 + ``` + ```julia + items² = items .^ 2 + ``` + ```julia + dot_product = items' * items + ``` + ```julia + matrix = items' .* items + ``` + ], + [ + Familiar imperative syntax + #v(2.1em) + *Broadcast* mechanism + #v(-0.2em) + ```julia + 91 + ``` + ```julia + 6×6 Matrix{Int64}: + 1 2 3 4 5 6 + 2 4 6 8 10 12 + 3 6 9 12 15 18 + 4 8 12 16 20 24 + 5 10 15 20 25 30 + 6 12 18 24 30 36 + ``` + ]) +] + +#slide(title:"Control flow and functions")[ + #grid(columns: (40%, 1fr), + [ + 'Blocks' return values + #v(-0.5em) + ```julia + x = if y > 0 + reduced = sqrt(y) + 2 * reduced + else + 4 + end + ``` + ],[ + String interpolation + #v(-0.5em) + ```julia + for s in ["hello", "bonjour", "hoi"] + greeting = uppercasefirst(s) + println("$greeting Julia!") + end + ``` + ] +) + Many ways to define a *function* + #set text(size: 23pt) + #v(-0.5em) + #grid( + columns: (55%, 45%), + [ + ```julia + function quadratic_solve(a, b, c) + Δ = √(b^2 - 4a * c) + root1 = (-b + Δ) / (2a) + root2 = (-b - Δ) / (2a) + return (root1, root2) + end + ``` + (The `return` is optional) + ],[ + Or more mathsy: + ```julia + f(x) = 5x^2 + 3x - 4 + ``` + Use whichever feels \ + best 😇 + ] +) +] + +#slide(title:"Side effects")[ + If a function *modifies* its arguments, it's name ends *by convention* with a *`!`* (called a "bang" 🧨) + #align(center)[ + ```julia + a = [7, 2, 9, 3, 5, 1, 8, 4, 5] + + b = sort(a) # does not touch `a` + sort!(a) # modifes `a` inplace + @assert a .== b + ``` + ] + #align(right, fat-text("Easier to reason about code")) + #boxed(fill-color:JULIA_BLUE, text(fill: SECONDARY_COLOR, [ + #v(0.2em) + Many functions have *`!`* alternatives. \ + This is not enforced, but common *convention*. + #v(0.2em) + ])) +] + +#slide(title: "")[ + #v(-6em) + #align(right, par(leading: 20pt, text(weight: "black", size: 160pt, juliafy("A first example")))) + #v(-4em) + #boxed(fill-color: JULIA_BLUE)[ + #v(0.2em) + See `examples/01-trapezoid-julia.jl`. *Compare* this to the Python implementation. + #v(0.2em) + ] +] + +#slide(title:"Why is Julia so fast?")[ + The #text(fill:JULIA_RED)[*compiler*] performs #text(fill: JULIA_GREEN)[*type inference*] on our code + - Compiles a *specialized* version for *inferred types* + - Generates *machine code* (JIT compiled) + - In practice: first time you call a function there's a small *compile time* overhead + - If the *types change*, the call stack is *recompiled* + #v(-0.5em) + #align(right, fat-text("Known as \"multiple dispatch\"")) + #v(-0.5em) + In Julia *multiple dispatch* is the *core idiom* + - Most languages have a *one definition rule* (ODR) + - ODR: a function can only have *one* implementation + - Some have *overloading* (C++ recently more sophisticated with C++20 Concepts) +] + +#slide(title:"A look at multiple dispatch")[ + ```julia + measure(x) = sqrt(x^2) + ``` + But what if my number is *complex*? + ```julia + measure(x::Complex) = sqrt(x.re^2 + x.im^2) + ``` + But what if my number is actually a *vector*? + ```julia + measure(x::Vector) = sqrt(x' * x) + ``` + #v(0.2em) + #align(right)[Retain the #text(fill: JULIA_RED)[*meaning*], focus on the #text(fill: JULIA_PURPLE)[*action*]] + Have the #text(fill: JULIA_GREEN)[*implementation*] do the #text(fill: JULIA_BLUE)[*right*] (or fast) thing + #grid( + columns: (27%, 33%, 1fr), [ + ```julia + measure(5.0) + ``` + ], [ + ```julia + measure(3 - 6im) + ``` + ], [ + ```julia + measure([5, 1, 8]) + ``` + ]) + #boxed(fill-color: white.darken(10%), align(center, fat-text("What's the compiler doing?"))) +] + +#slide(title: "Inspecting deeper")[ + Meet some *new friends* 🐴 🐬: + #grid( + columns: (23%, 23%, 1fr), + [ ```julia + typeof(x) + ``` ], + [ ```julia + methods(f) + ``` ], + [ ```julia + @code_warntype f(x) + ``` ], + ) + They show us what the *compiler* sees and uses: + #grid( + columns: (30%, 1fr), + column-gutter: 3em, + [ + ```julia + julia> typeof(5.0) + Float64 + julia> typeof(5) + Int64 + ``` + ],[ + ```julia + julia> methods(measure) + # 3 methods for generic function + "measure" from Main: + [1] measure(x::Vector) + @ REPL[15]:1 + [2] measure(x::Complex) + @ REPL[14]:1 + [3] measure(x) + @ REPL[13]:1 + ``` + ] +) +] + +#slide(title:"@code_warntype")[ + See the *types inferred* by the compiler + #set align(center) + ```julia + julia> @code_warntype measure([5, 1, 8]) + MethodInstance for measure(::Vector{Int64}) + from measure(x::Vector) @ Main REPL[15]:1 + Arguments + #self#::Core.Const(measure) + x::Vector{Int64} + Body::Float64 + 1 ─ %1 = Main.:var"'"(x)::LinearAlgebra.Adjoint{Int64, Vector{Int64}} + │ %2 = (%1 * x)::Int64 + │ %3 = Main.sqrt(%2)::Float64 + └── return %3 + ``` +] + +#slide(title:"The compiler")[ + #block( + move(dx: 2.5em, image("figs/julia-source-to-native.png", width: 90%)) + ) + #align(right, text(size: 12pt, "Image: Carsten Bauer")) +] + +#slide(title:"")[ + #v(-6em) + #align(right, par(leading: 20pt, text(weight: "black", size: 140pt, juliafy("Going nowhere faster")))) + #v(-5.5em) + #boxed(fill-color: JULIA_BLUE)[ + #v(0.2em) + See `examples/02-threaded-julia.jl` for an example of `@threads` macro. + #v(0.2em) + ] +] + +#slide(title:"Aside: automatic differentiation", title-size: 42pt)[ + #set align(center) + There's an excellent video: \ + https://www.youtube.com/watch?v=vAp6nUMrKYg + #image("./figs/auto-diff-youtube.png", width: 80%) + Go watch it! +] + +#slide(title:"AD crash course", title-size: 42pt)[ + A *magical way* of taking derivatives of functions + #boxed(fill-color: JULIA_PURPLE)[ + #v(0.2em) + Use a *dual number*, as in $x + dif x$. (Ab)use the *chain rule*. + #v(0.2em) + ] + + $ + dif (x + y) &arrow.r.bar dif x + dif y \ + dif (x y) &arrow.r.bar dif x #h(6pt) y + x #h(3pt)dif y + $ + Implementing in Julia: + #text(size: 22pt)[ + #grid(columns: (30%, 1fr), + [ ```julia + struct Dual + x::Float64 + dx::Float64 + end + ``` ],[ + ```julia + x::Dual + y::Dual = + Dual(x.x + y.x, x.dx + y.dx) + x::Dual * y::Dual = + Dual(x.x * y.x, x.dx * y.x + x.x * y.dx) + # and `/` `^` ... left to the reader + ``` + ]) +] + With *multiple dispatch* we can use it on existing functions! +] + +#slide(title:"Example: extrema")[ + Don't reinvent the wheel, *ForwardDiff.jl* has all we need: + #align(center, text(size: 22pt)[ + ```julia + using ForwardDiff + f(x) = x^5 - 4x^3 + x^2 - 3 + @assert 36 == ForwardDiff.derivative(f, 2) + ``` + ]) + Root finding + #v(-0.5em) + + #grid(columns: (60%, 1fr), + text(size: 22pt)[ + ```julia + function newton_root(f, x₀; N = 10) + df(x) = ForwardDiff.derivative(f, x) + for i in 1:N + x₀ -= f(x₀) / df(x₀) + end + return x₀ + end + ``` + ], + block[ + Find extrema with: $f'(x) = 0$ + #v(1em) + #fat-text("Try it out!") + ] +) + + #boxed(fill-color: JULIA_GREEN)[ + See `examples/03-root-finding.jl` for an example. + ] +] + +#slide(title:"Julia for astrophysics")[ + #v(-0.3em) + There's a growing *JuliaAstro* community full of wonderful people ✨🔭 + #boxed(fill-color: JULIA_GREEN)[ + #v(0.2em) + Julia is *excellent* for data science, optimization problems, differential equation, machine learning... + #v(0.2em) +] + Multiple dispatch is teaming with *emergent features*, propagate uncertainties just like dual numbers with *Measurements.jl*, or units with *Unitful.jl* + - Easy access to various accelerator backends + - Pandas-like *DataFrames.jl* and ML in *Lux.jl* + - Interoperate with your favourite Python packages, but do the heavy lifting in *Julia* + - High degree of *reproducibility* thanks to *Pkg.jl* +] + +#slide(title:"But maybe why not Julia?")[ + Learning a *new* language can be difficult, especially one as *different* as Julia + - *Pre-compile* times can be frustrating + - Sometimes *error reporting* is a mess + - Ecosystem *maturity* still growing + - Type stability can be subtle and insanity inducing (c.f. Cthulhu.jl) + #boxed(fill-color: JULIA_GREEN)[ + #v(0.2em) + But it's steadily *getting better*, and seeing *widespread adoption* + #v(0.2em) + ] + Worth glancing at #link("https://julialang.org/blog/2022/02/10years/")[Why we use Julia, 10 years later]. +] + +#slide(title:"Where to find more")[ + #boxed(fill-color: JULIA_GREEN)[ + #v(0.2em) + #align(center)[*Ask me* (at the pub later 🫶)] + #v(0.2em) + ] + #v(-1.0em) + #boxed(fill-color: JULIA_BLUE)[ + #v(0.2em) + #align(center)[Ask your colleagues *Andy*, *Gloria*, *Matt* ...] + #v(0.2em) + ] + The #link("https://docs.julialang.org/en/v1/")[Julia Documentation] is full of good things! + - As is the #link("https://docs.sciml.ai/Overview/stable/")[SciML documentation] + - I wrote a #link("https://github.com/RSE-Cambridge/julia-study-group/wiki/Resources")[list of resources] for the Cambridge RSE group + Checkout the #link("https://www.youtube.com/user/JuliaLanguage")[Julia YouTube channel] and join the *Slack*! + Open *meetup suggestions* for Julia topics in our #link("https://github.com/astro-group-bristol/developer-group")[Astro Developer Group]. + #boxed(fill-color: JULIA_PURPLE)[ + #v(0.2em) + #align(center)[Keep an eye out for *JuliaCon* 2024!] + #v(0.2em) + ] +] + +#slide(title: "")[ + #v(-6em) + #align(right, par(leading: 25pt, text(weight: "black", size: 160pt, juliafy("Thank you for listening")))) + #v(-4em) +] diff --git a/src/tamburlaine.typ b/src/tamburlaine.typ new file mode 100644 index 0000000..18a4e07 --- /dev/null +++ b/src/tamburlaine.typ @@ -0,0 +1,121 @@ +#import "@preview/polylux:0.3.1": * + +#let SECONDARY_COLOR = rgb("#f6f0e0").lighten(90%) +#let PRIMARY_COLOR = rgb("#bf2f38") +#let TEXT_COLOR = black.lighten(13%) + +#let JULIA_RED = rgb("#c93b31") +#let JULIA_PURPLE = rgb("#9158a2") +#let JULIA_GREEN = rgb("#389645") +#let JULIA_BLUE = rgb("#4063d8") + +#let tamburlaine-theme(aspect-ratio: "4-3", body) = { + set page( + paper: "presentation-" + aspect-ratio, + fill: SECONDARY_COLOR, + margin: 1em + ) + set text(fill: TEXT_COLOR, size: 25pt, font: "Montserrat") + body +} + +#let juliafy(string) = { + let colors = (JULIA_RED, JULIA_GREEN, JULIA_PURPLE, JULIA_BLUE) + string.split().enumerate().map(item => { + let (i, t) = item + text(fill: colors.at(calc.rem(i, colors.len())), t) + }).join(" ") +} + +#let title-slide( + title: none, + authors: (), + where: none, + date: datetime.today(), +) = { + set page( + fill: SECONDARY_COLOR, + margin: 1em, + ) + set text(fill: TEXT_COLOR, weight: "bold") + + let author = authors.join(h(1em)) + + logic.polylux-slide[ + #rect(inset:(top: 1em), width:100%, height: 74%, stroke:none)[ + #align(right)[ + #title + ] + ] + #v(-0.6em) + + #line(length: 100%, stroke: 5mm + TEXT_COLOR) + #v(-0.5em) + #grid( + columns: (70%, 30%), + row-gutter: 15pt, + author, + move(dx:0.2em, where), + align(left, text(size: 20pt, weight: "regular")[University of Bristol]), + align(right, text(size: 20pt, weight: "regular", + date.display("[day] [month repr:long] [year]") + )), + ) + #v(-0.1em) + #line(length: 100%, stroke: 8mm + TEXT_COLOR) + ] +} + +// eh good enough +#let global_date = datetime(year: 2024, month: 4, day: 26) + +#let slide(title: none, title-size: 50pt,body) = { + set page( + fill: SECONDARY_COLOR, + margin: (top: 1em, bottom: 1.5em, left: 1em, right: 1em) + ) + let header = align(top, locate( loc => { + set text(size: 20pt) + grid( + columns: (1fr, 1fr), + align(horizon + right, grid( + columns: 1, rows: 1em, + title, + utils.current-section, + )) + ) + })) + + let footer = locate( loc => { + block( + stroke: ( top: 1mm + TEXT_COLOR ), width: 100%, inset: ( y: .4em ), + text(.5em, { + "Fergus Baker" + h(2em) + "/" + h(2em) + "Astro Dev Group" + h(2em) + "/" + h(2em) + global_date.display("[day] [month repr:long] [year]") + h(1fr) + logic.logical-slide.display() + }) + ) + }) + + set page( + footer: footer, + footer-descent: 0em, + header-ascent: 1.5em, + ) + + let content = { + block(spacing: 0.0em, text(size: title-size, weight: "black", juliafy(title))) + body + } + + logic.polylux-slide(content) +} +