Rust native benchmark: drop unused dependencies

Also, drop the commented-out beginnings of a `plotters-gtk4` version. I
can't use `plotters-gtk4` on my machine because it requires GTK 4.14 or
higher, and Ubuntu 22.04 is still at GTK 4.6.

lang-trials/rust-benchmark-native/.gitignore

@@ -0,0 +1,3 @@
+target/*
+dist/*
+Cargo.lock

lang-trials/rust-benchmark-native/Cargo.toml

@@ -0,0 +1,16 @@
+[package]
+name = "rust-benchmark-native"
+version = "0.1.0"
+authors = ["Aaron"]
+edition = "2021"
+
+[dependencies]
+cairo-rs = "0.20.1"
+gtk = { package = "gtk4", version = "0.9.0" }
+nalgebra = "0.33.0"
+plotters = "0.3.6"
+plotters-cairo = "0.7.0"
+
+[profile.release]
+opt-level = "s" # optimize for small code size
+debug = true # include debug symbols

lang-trials/rust-benchmark-native/src/engine.rs

@@ -0,0 +1,105 @@
+use nalgebra::{*, allocator::Allocator};
+use std::f64::consts::{PI, E};
+
+/* dynamic matrices */
+pub fn rand_eigval_series(dim: usize, time_res: usize) -> Vec<OVector<Complex<f64>, Dyn>> {
+    // initialize the random matrix
+    let mut rand_mat = DMatrix::<f64>::from_fn(dim, dim, |j, k| {
+        let n = j*dim + k;
+        E*((n*n) as f64) % 2.0 - 1.0
+    }) * (3.0 / (dim as f64)).sqrt();
+    
+    // initialize the rotation step
+    let mut rot_step = DMatrix::<f64>::identity(dim, dim);
+    let max_freq = 4;
+    for n in (0..dim).step_by(2) {
+        let ang = PI * ((n % max_freq) as f64) / (time_res as f64);
+        let ang_cos = ang.cos();
+        let ang_sin = ang.sin();
+        rot_step[(n, n)] = ang_cos;
+        rot_step[(n+1, n)] = ang_sin;
+        rot_step[(n, n+1)] = -ang_sin;
+        rot_step[(n+1, n+1)] = ang_cos;
+    }
+    
+    // find the eigenvalues
+    let mut eigval_series = Vec::<OVector<Complex<f64>, Dyn>>::with_capacity(time_res);
+    eigval_series.push(rand_mat.complex_eigenvalues());
+    for _ in 1..time_res {
+        rand_mat = &rot_step * rand_mat;
+        eigval_series.push(rand_mat.complex_eigenvalues());
+    }
+    eigval_series
+}
+
+/* dynamic single float matrices */
+/*pub fn rand_eigval_series(dim: usize, time_res: usize) -> Vec<OVector<Complex<f32>, Dyn>> {
+    // initialize the random matrix
+    let mut rand_mat = DMatrix::<f32>::from_fn(dim, dim, |j, k| {
+        let n = j*dim + k;
+        (E as f32)*((n*n) as f32) % 2.0_f32 - 1.0_f32
+    }) * (3.0_f32 / (dim as f32)).sqrt();
+    
+    // initialize the rotation step
+    let mut rot_step = DMatrix::<f32>::identity(dim, dim);
+    let max_freq = 4;
+    for n in (0..dim).step_by(2) {
+        let ang = (PI as f32) * ((n % max_freq) as f32) / (time_res as f32);
+        let ang_cos = ang.cos();
+        let ang_sin = ang.sin();
+        rot_step[(n, n)] = ang_cos;
+        rot_step[(n+1, n)] = ang_sin;
+        rot_step[(n, n+1)] = -ang_sin;
+        rot_step[(n+1, n+1)] = ang_cos;
+    }
+    
+    // find the eigenvalues
+    let mut eigval_series = Vec::<OVector<Complex<f32>, Dyn>>::with_capacity(time_res);
+    eigval_series.push(rand_mat.complex_eigenvalues());
+    for _ in 1..time_res {
+        rand_mat = &rot_step * rand_mat;
+        eigval_series.push(rand_mat.complex_eigenvalues());
+    }
+    eigval_series
+}*/
+
+/* static matrices. should only be used when the dimension is really small */
+/*pub fn rand_eigval_series<N>(time_res: usize) -> Vec<OVector<Complex<f64>, N>>
+    where
+        N: ToTypenum + DimName + DimSub<U1>,
+        DefaultAllocator:
+            Allocator<N> +
+            Allocator<N, N> +
+            Allocator<<N as DimSub<U1>>::Output> +
+            Allocator<N, <N as DimSub<U1>>::Output>
+{
+    // initialize the random matrix
+    let dim = N::try_to_usize().unwrap();
+    let mut rand_mat = OMatrix::<f64, N, N>::from_fn(|j, k| {
+        let n = j*dim + k;
+        E*((n*n) as f64) % 2.0 - 1.0
+    }) * (3.0 / (dim as f64)).sqrt();
+    /*let mut rand_mat = OMatrix::<f64, N, N>::identity();*/
+    
+    // initialize the rotation step
+    let mut rot_step = OMatrix::<f64, N, N>::identity();
+    let max_freq = 4;
+    for n in (0..dim).step_by(2) {
+        let ang = PI * ((n % max_freq) as f64) / (time_res as f64);
+        let ang_cos = ang.cos();
+        let ang_sin = ang.sin();
+        rot_step[(n, n)] = ang_cos;
+        rot_step[(n+1, n)] = ang_sin;
+        rot_step[(n, n+1)] = -ang_sin;
+        rot_step[(n+1, n+1)] = ang_cos;
+    }
+    
+    // find the eigenvalues
+    let mut eigval_series = Vec::<OVector<Complex<f64>, N>>::with_capacity(time_res);
+    eigval_series.push(rand_mat.complex_eigenvalues());
+    for _ in 1..time_res {
+        rand_mat = &rot_step * rand_mat;
+        eigval_series.push(rand_mat.complex_eigenvalues());
+    }
+    eigval_series
+}*/

lang-trials/rust-benchmark-native/src/main.rs

@@ -0,0 +1,104 @@
+// based on Olivier Pelhatre's GTK 3 example, ported to GTK 4
+//
+//   https://github.com/Ouam74/RUST_Real-time_plots_using_GTK-rs_and_Plotters-rs
+//
+// a self-contained component might draw on the example below, by StackOverflow
+// user Nicolas
+//
+//   https://stackoverflow.com/a/76548487
+//
+// here's a crash course in `plotters`
+//
+//   https://plotters-rs.github.io/book/basic/basic_data_plotting.html
+//
+
+extern crate cairo;
+use plotters::prelude::*;
+use plotters_cairo::CairoBackend;
+use gtk::{
+    glib,
+    prelude::*,
+    Adjustment,
+    Align,
+    Application,
+    ApplicationWindow,
+    Box,
+    DrawingArea,
+    Label,
+    Orientation,
+    Scale
+};
+use std::time::Instant;
+
+mod engine;
+
+fn main() -> glib::ExitCode {
+    let app = Application::builder()
+        .application_id("org.studioinfinity.rust-benchmark-native")
+        .build();
+    
+    app.connect_activate(|app| {
+        const TIME_RES: usize = 100;
+        let start_time = Instant::now();
+        let eigval_series = engine::rand_eigval_series(60, TIME_RES);
+        let run_time = start_time.elapsed().as_millis();
+        
+        // application state
+        let time_step = Adjustment::new(0.0, 0.0, TIME_RES as f64, 1.0, 0.0, 0.0);
+        
+        // create the window.
+        let window = ApplicationWindow::builder()
+            .application(app)
+            .title("The circular law")
+            .build();
+        
+        // create a vertical box
+        let container = Box::new(Orientation::Vertical, 5);
+        window.set_child(Some(&container));
+        
+        // create the run time readout
+        let run_time_readout = Label::builder()
+            .margin_top(5)
+            .margin_start(10)
+            .halign(Align::Start)
+            .label(glib::gformat!("{} ms", run_time))
+            .build();
+        container.append(&run_time_readout);
+        
+        // set up the drawing area
+        let drawing_area = DrawingArea::builder()
+            .content_width(600)
+            .content_height(600)
+            .build();
+        let time_step_for_draw = time_step.clone();
+        let draw_eigvals = move |_: &DrawingArea, context: &cairo::Context, width: i32, height: i32| {
+            let root = CairoBackend::new(&context, (width as u32, height as u32)).unwrap().into_drawing_area();
+            let _ = root.fill(&BLACK);
+            
+            const R_DISP: f64 = 1.5;
+            let mut chart = ChartBuilder::on(&root)
+                .build_cartesian_2d(-R_DISP..R_DISP, -R_DISP..R_DISP)
+                .unwrap();
+            let time_step_val = (time_step_for_draw.value() as usize).min(TIME_RES-1);
+            let eigval_iter = eigval_series[time_step_val].iter();
+            let _ = chart.draw_series(
+                eigval_iter.map(|z| Circle::new((z.re, z.im), 3, WHITE.filled()))
+            );
+            let _ = root.present();
+        };
+        DrawingAreaExtManual::set_draw_func(&drawing_area, draw_eigvals);
+        container.append(&drawing_area);
+        
+        // set up the time step slider
+        let time_step_scale = Scale::new(Orientation::Horizontal, Some(&time_step));
+        time_step_scale.connect_value_changed(move |_: &Scale| {
+            drawing_area.queue_draw();
+        });
+        container.append(&time_step_scale);
+        
+        // show the window
+        window.present();
+    });
+    
+    app.run()
+}

lang-trials/rust-benchmark/Cargo.toml

@@ -1,5 +1,5 @@
 [package]
-name = "sycamore-trial"
+name = "rust-benchmark"
 version = "0.1.0"
 authors = ["Aaron"]
 edition = "2021"
@@ -10,7 +10,6 @@ default = ["console_error_panic_hook"]
 [dependencies]
 nalgebra = "0.33.0"
 sycamore = "0.9.0-beta.2"
-typenum = "1.17.0"
 
 # The `console_error_panic_hook` crate provides better debugging of panics by
 # logging them with `console.error`. This is great for development, but requires

lang-trials/rust-benchmark/src/engine.rs

@@ -1,20 +1,9 @@
 use nalgebra::{*, allocator::Allocator};
 use std::f64::consts::{PI, E};
-/*use std::ops::Sub;*/
-/*use typenum::{B1, UInt, UTerm};*/
 
 /* dynamic matrices */
-pub fn rand_eigval_series<N>(time_res: usize) -> Vec<OVector<Complex<f64>, Dyn>>
-    where
-        N: ToTypenum + DimName + DimSub<U1>,
-        DefaultAllocator:
-            Allocator<N> +
-            Allocator<N, N> +
-            Allocator<<N as DimSub<U1>>::Output> +
-            Allocator<N, <N as DimSub<U1>>::Output>
-{
+pub fn rand_eigval_series(dim: usize, time_res: usize) -> Vec<OVector<Complex<f64>, Dyn>> {
     // initialize the random matrix
-    let dim = N::try_to_usize().unwrap();
     let mut rand_mat = DMatrix::<f64>::from_fn(dim, dim, |j, k| {
         let n = j*dim + k;
         E*((n*n) as f64) % 2.0 - 1.0
@@ -44,17 +33,8 @@ pub fn rand_eigval_series<N>(time_res: usize) -> Vec<OVector<Complex<f64>, Dyn>>
 }
 
 /* dynamic single float matrices */
-/*pub fn rand_eigval_series<N>(time_res: usize) -> Vec<OVector<Complex<f32>, Dyn>>
-    where
-        N: ToTypenum + DimName + DimSub<U1>,
-        DefaultAllocator:
-            Allocator<N> +
-            Allocator<N, N> +
-            Allocator<<N as DimSub<U1>>::Output> +
-            Allocator<N, <N as DimSub<U1>>::Output>
-{
+/*pub fn rand_eigval_series(dim: usize, time_res: usize) -> Vec<OVector<Complex<f32>, Dyn>> {
     // initialize the random matrix
-    let dim = N::try_to_usize().unwrap();
     let mut rand_mat = DMatrix::<f32>::from_fn(dim, dim, |j, k| {
         let n = j*dim + k;
         (E as f32)*((n*n) as f32) % 2.0_f32 - 1.0_f32
@@ -99,7 +79,6 @@ pub fn rand_eigval_series<N>(time_res: usize) -> Vec<OVector<Complex<f64>, Dyn>>
         let n = j*dim + k;
         E*((n*n) as f64) % 2.0 - 1.0
     }) * (3.0 / (dim as f64)).sqrt();
-    /*let mut rand_mat = OMatrix::<f64, N, N>::identity();*/
     
     // initialize the rotation step
     let mut rot_step = OMatrix::<f64, N, N>::identity();
@@ -123,42 +102,3 @@ pub fn rand_eigval_series<N>(time_res: usize) -> Vec<OVector<Complex<f64>, Dyn>>
     }
     eigval_series
 }*/
-
-/* another attempt at static matrices. i couldn't get the types to work out */
-/*pub fn random_eigval_series<const N: usize>(time_res: usize) -> Vec<OVector<Complex<f64>, Const<N>>>
-    where
-        Const<N>: ToTypenum,
-        <Const<N> as ToTypenum>::Typenum: Sub<UInt<UTerm, B1>>,
-        <<Const<N> as ToTypenum>::Typenum as Sub<UInt<UTerm, B1>>>::Output: ToConst
-{
-    // initialize the random matrix
-    /*let mut rand_mat = SMatrix::<f64, N, N>::zeros();
-    for n in 0..N*N {
-        rand_mat[n] = E*((n*n) as f64) % 2.0 - 1.0;
-    }*/
-    let rand_mat = OMatrix::<f64, Const<N>, Const<N>>::from_fn(|j, k| {
-        let n = j*N + k;
-        E*((n*n) as f64) % 2.0 - 1.0
-    });
-    
-    // initialize the rotation step
-    let mut rot_step = OMatrix::<f64, Const<N>, Const<N>>::identity();
-    let max_freq = 4;
-    for n in (0..N).step_by(2) {
-        let ang = PI * ((n % max_freq) as f64) / (time_res as f64);
-        let ang_cos = ang.cos();
-        let ang_sin = ang.sin();
-        rot_step[(n, n)] = ang_cos;
-        rot_step[(n+1, n)] = ang_sin;
-        rot_step[(n, n+1)] = -ang_sin;
-        rot_step[(n+1, n+1)] = ang_cos;
-    }
-    
-    // find the eigenvalues
-    let mut eigvals = Vec::<OVector<Complex<f64>, Const<N>>>::with_capacity(time_res);
-    unsafe { eigvals.set_len(time_res); }
-    for t in 0..time_res {
-        eigvals[t] = rand_mat.complex_eigenvalues();
-    }
-    eigvals
-}*/

lang-trials/rust-benchmark/src/main.rs

@@ -1,4 +1,3 @@
-use nalgebra::*;
 use std::f64::consts::PI as PI;
 use sycamore::{prelude::*, rt::{JsCast, JsValue}};
 use web_sys::window;
@@ -19,7 +18,8 @@ fn main() {
         on_mount(move || {
             let performance = window().unwrap().performance().unwrap();
             let start_time = performance.now();
-            let eigval_series = engine::rand_eigval_series::<U60>(time_res);
+            /*let eigval_series = engine::rand_eigval_series::<U60>(time_res);*/
+            let eigval_series = engine::rand_eigval_series(60, time_res);
             let run_time = performance.now() - start_time;
             run_time_report.set(run_time);