Rust benchmark: write native version
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lang-trials/rust-benchmark-native/.gitignore
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lang-trials/rust-benchmark-native/.gitignore
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target/*
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dist/*
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Cargo.lock
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18
lang-trials/rust-benchmark-native/Cargo.toml
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lang-trials/rust-benchmark-native/Cargo.toml
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[package]
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name = "rust-benchmark-native"
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version = "0.1.0"
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authors = ["Aaron"]
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edition = "2021"
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[dependencies]
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cairo-rs = "0.20.1"
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gtk = { package = "gtk4", version = "0.9.0" }
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##minifb = "0.27.0"
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nalgebra = "0.33.0"
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plotters = "0.3.6"
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plotters-cairo = "0.7.0"
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##plotters-gtk4 = { git = "https://github.com/baarkerlounger/plotters-gtk4.git", branch = "patch-1" }
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[profile.release]
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opt-level = "s" # optimize for small code size
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debug = true # include debug symbols
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lang-trials/rust-benchmark-native/src/engine.rs
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lang-trials/rust-benchmark-native/src/engine.rs
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use nalgebra::{*, allocator::Allocator};
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use std::f64::consts::{PI, E};
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/* dynamic matrices */
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pub fn rand_eigval_series(dim: usize, time_res: usize) -> Vec<OVector<Complex<f64>, Dyn>> {
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// initialize the random matrix
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let mut rand_mat = DMatrix::<f64>::from_fn(dim, dim, |j, k| {
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let n = j*dim + k;
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E*((n*n) as f64) % 2.0 - 1.0
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}) * (3.0 / (dim as f64)).sqrt();
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// initialize the rotation step
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let mut rot_step = DMatrix::<f64>::identity(dim, dim);
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let max_freq = 4;
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for n in (0..dim).step_by(2) {
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let ang = PI * ((n % max_freq) as f64) / (time_res as f64);
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let ang_cos = ang.cos();
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let ang_sin = ang.sin();
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rot_step[(n, n)] = ang_cos;
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rot_step[(n+1, n)] = ang_sin;
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rot_step[(n, n+1)] = -ang_sin;
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rot_step[(n+1, n+1)] = ang_cos;
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}
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// find the eigenvalues
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let mut eigval_series = Vec::<OVector<Complex<f64>, Dyn>>::with_capacity(time_res);
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eigval_series.push(rand_mat.complex_eigenvalues());
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for _ in 1..time_res {
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rand_mat = &rot_step * rand_mat;
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eigval_series.push(rand_mat.complex_eigenvalues());
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}
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eigval_series
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}
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/* dynamic single float matrices */
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/*pub fn rand_eigval_series(dim: usize, time_res: usize) -> Vec<OVector<Complex<f32>, Dyn>> {
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// initialize the random matrix
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let mut rand_mat = DMatrix::<f32>::from_fn(dim, dim, |j, k| {
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let n = j*dim + k;
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(E as f32)*((n*n) as f32) % 2.0_f32 - 1.0_f32
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}) * (3.0_f32 / (dim as f32)).sqrt();
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// initialize the rotation step
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let mut rot_step = DMatrix::<f32>::identity(dim, dim);
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let max_freq = 4;
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for n in (0..dim).step_by(2) {
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let ang = (PI as f32) * ((n % max_freq) as f32) / (time_res as f32);
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let ang_cos = ang.cos();
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let ang_sin = ang.sin();
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rot_step[(n, n)] = ang_cos;
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rot_step[(n+1, n)] = ang_sin;
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rot_step[(n, n+1)] = -ang_sin;
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rot_step[(n+1, n+1)] = ang_cos;
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}
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// find the eigenvalues
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let mut eigval_series = Vec::<OVector<Complex<f32>, Dyn>>::with_capacity(time_res);
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eigval_series.push(rand_mat.complex_eigenvalues());
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for _ in 1..time_res {
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rand_mat = &rot_step * rand_mat;
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eigval_series.push(rand_mat.complex_eigenvalues());
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}
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eigval_series
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}*/
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/* static matrices. should only be used when the dimension is really small */
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/*pub fn rand_eigval_series<N>(time_res: usize) -> Vec<OVector<Complex<f64>, N>>
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where
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N: ToTypenum + DimName + DimSub<U1>,
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DefaultAllocator:
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Allocator<N> +
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Allocator<N, N> +
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Allocator<<N as DimSub<U1>>::Output> +
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Allocator<N, <N as DimSub<U1>>::Output>
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{
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// initialize the random matrix
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let dim = N::try_to_usize().unwrap();
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let mut rand_mat = OMatrix::<f64, N, N>::from_fn(|j, k| {
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let n = j*dim + k;
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E*((n*n) as f64) % 2.0 - 1.0
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}) * (3.0 / (dim as f64)).sqrt();
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/*let mut rand_mat = OMatrix::<f64, N, N>::identity();*/
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// initialize the rotation step
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let mut rot_step = OMatrix::<f64, N, N>::identity();
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let max_freq = 4;
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for n in (0..dim).step_by(2) {
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let ang = PI * ((n % max_freq) as f64) / (time_res as f64);
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let ang_cos = ang.cos();
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let ang_sin = ang.sin();
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rot_step[(n, n)] = ang_cos;
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rot_step[(n+1, n)] = ang_sin;
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rot_step[(n, n+1)] = -ang_sin;
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rot_step[(n+1, n+1)] = ang_cos;
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}
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// find the eigenvalues
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let mut eigval_series = Vec::<OVector<Complex<f64>, N>>::with_capacity(time_res);
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eigval_series.push(rand_mat.complex_eigenvalues());
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for _ in 1..time_res {
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rand_mat = &rot_step * rand_mat;
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eigval_series.push(rand_mat.complex_eigenvalues());
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}
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eigval_series
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}*/
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lang-trials/rust-benchmark-native/src/main.rs
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lang-trials/rust-benchmark-native/src/main.rs
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// based on Olivier Pelhatre's GTK 3 example, ported to GTK 4
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//
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// https://github.com/Ouam74/RUST_Real-time_plots_using_GTK-rs_and_Plotters-rs
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//
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// a self-contained component might draw on the example below, by StackOverflow
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// user Nicolas
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//
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// https://stackoverflow.com/a/76548487
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//
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// here's a crash course in `plotters`
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//
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// https://plotters-rs.github.io/book/basic/basic_data_plotting.html
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//
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extern crate cairo;
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use plotters::prelude::*;
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use plotters_cairo::CairoBackend;
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use gtk::{
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glib,
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prelude::*,
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Adjustment,
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Align,
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Application,
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ApplicationWindow,
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Box,
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DrawingArea,
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Label,
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Orientation,
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/*Picture,*/
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Scale
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};
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/*use plotters_gtk4::Paintable;*/
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use std::time::Instant;
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mod engine;
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fn main() -> glib::ExitCode {
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let app = Application::builder()
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.application_id("org.studioinfinity.rust-benchmark-native")
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.build();
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app.connect_activate(|app| {
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/* run time is typically 77 ms, but at one point i was consistently
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getting more like 260 ms. it's not clear what was causing that. building
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from scratch seemed to give the short run time, and waiting a while
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since the last build might also have had some effect */
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const TIME_RES: usize = 100;
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let start_time = Instant::now();
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let eigval_series = engine::rand_eigval_series(60, TIME_RES);
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let run_time = start_time.elapsed().as_millis();
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// application state
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let time_step = Adjustment::new(0.0, 0.0, TIME_RES as f64, 1.0, 0.0, 0.0);
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// create the window.
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let window = ApplicationWindow::builder()
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.application(app)
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.title("The circular law")
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.build();
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// create a vertical box
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let container = Box::new(Orientation::Vertical, 5);
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window.set_child(Some(&container));
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// create the run time readout
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let run_time_readout = Label::builder()
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.margin_top(5)
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.margin_start(10)
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.halign(Align::Start)
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.label(glib::gformat!("{} ms", run_time))
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.build();
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container.append(&run_time_readout);
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// set up the drawing area
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let drawing_area = DrawingArea::builder()
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.content_width(600)
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.content_height(600)
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.build();
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let time_step_for_draw = time_step.clone();
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let draw_eigvals = move |_: &DrawingArea, context: &cairo::Context, width: i32, height: i32| {
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let root = CairoBackend::new(&context, (width as u32, height as u32)).unwrap().into_drawing_area();
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let _ = root.fill(&BLACK);
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const R_DISP: f64 = 1.5;
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let mut chart = ChartBuilder::on(&root)
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.build_cartesian_2d(-R_DISP..R_DISP, -R_DISP..R_DISP)
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.unwrap();
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let time_step_val = (time_step_for_draw.value() as usize).min(TIME_RES-1);
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let eigval_iter = eigval_series[time_step_val].iter();
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let _ = chart.draw_series(
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eigval_iter.map(|z| Circle::new((z.re, z.im), 3, WHITE.filled()))
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);
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let _ = root.present();
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};
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DrawingAreaExtManual::set_draw_func(&drawing_area, draw_eigvals);
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container.append(&drawing_area);
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// set up the time step slider
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let time_step_scale = Scale::new(Orientation::Horizontal, Some(&time_step));
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time_step_scale.connect_value_changed(move |_: &Scale| {
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drawing_area.queue_draw();
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});
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container.append(&time_step_scale);
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// show the window
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window.present();
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});
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app.run()
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}
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