forked from StudioInfinity/dyna3
Compare commits
No commits in common. "8cb73f88d0726dd56d11bc62397d7ff0c4297a03" and "144bfb8faf69fc3ebeb5051c4053e25f8726103b" have entirely different histories.
8cb73f88d0
...
144bfb8faf
7 changed files with 66 additions and 233 deletions
3
lang-trials/rust-benchmark-native/.gitignore
vendored
3
lang-trials/rust-benchmark-native/.gitignore
vendored
|
@ -1,3 +0,0 @@
|
||||||
target/*
|
|
||||||
dist/*
|
|
||||||
Cargo.lock
|
|
|
@ -1,16 +0,0 @@
|
||||||
[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
|
|
|
@ -1,105 +0,0 @@
|
||||||
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
|
|
||||||
}*/
|
|
|
@ -1,104 +0,0 @@
|
||||||
// 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()
|
|
||||||
}
|
|
|
@ -1,5 +1,5 @@
|
||||||
[package]
|
[package]
|
||||||
name = "rust-benchmark"
|
name = "sycamore-trial"
|
||||||
version = "0.1.0"
|
version = "0.1.0"
|
||||||
authors = ["Aaron"]
|
authors = ["Aaron"]
|
||||||
edition = "2021"
|
edition = "2021"
|
||||||
|
@ -10,6 +10,7 @@ default = ["console_error_panic_hook"]
|
||||||
[dependencies]
|
[dependencies]
|
||||||
nalgebra = "0.33.0"
|
nalgebra = "0.33.0"
|
||||||
sycamore = "0.9.0-beta.2"
|
sycamore = "0.9.0-beta.2"
|
||||||
|
typenum = "1.17.0"
|
||||||
|
|
||||||
# The `console_error_panic_hook` crate provides better debugging of panics by
|
# The `console_error_panic_hook` crate provides better debugging of panics by
|
||||||
# logging them with `console.error`. This is great for development, but requires
|
# logging them with `console.error`. This is great for development, but requires
|
||||||
|
|
|
@ -1,9 +1,20 @@
|
||||||
use nalgebra::{*, allocator::Allocator};
|
use nalgebra::{*, allocator::Allocator};
|
||||||
use std::f64::consts::{PI, E};
|
use std::f64::consts::{PI, E};
|
||||||
|
/*use std::ops::Sub;*/
|
||||||
|
/*use typenum::{B1, UInt, UTerm};*/
|
||||||
|
|
||||||
/* dynamic matrices */
|
/* dynamic matrices */
|
||||||
pub fn rand_eigval_series(dim: usize, time_res: usize) -> Vec<OVector<Complex<f64>, Dyn>> {
|
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>
|
||||||
|
{
|
||||||
// initialize the random matrix
|
// initialize the random matrix
|
||||||
|
let dim = N::try_to_usize().unwrap();
|
||||||
let mut rand_mat = DMatrix::<f64>::from_fn(dim, dim, |j, k| {
|
let mut rand_mat = DMatrix::<f64>::from_fn(dim, dim, |j, k| {
|
||||||
let n = j*dim + k;
|
let n = j*dim + k;
|
||||||
E*((n*n) as f64) % 2.0 - 1.0
|
E*((n*n) as f64) % 2.0 - 1.0
|
||||||
|
@ -33,8 +44,17 @@ pub fn rand_eigval_series(dim: usize, time_res: usize) -> Vec<OVector<Complex<f6
|
||||||
}
|
}
|
||||||
|
|
||||||
/* dynamic single float matrices */
|
/* dynamic single float matrices */
|
||||||
/*pub fn rand_eigval_series(dim: usize, time_res: usize) -> Vec<OVector<Complex<f32>, Dyn>> {
|
/*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>
|
||||||
|
{
|
||||||
// initialize the random matrix
|
// initialize the random matrix
|
||||||
|
let dim = N::try_to_usize().unwrap();
|
||||||
let mut rand_mat = DMatrix::<f32>::from_fn(dim, dim, |j, k| {
|
let mut rand_mat = DMatrix::<f32>::from_fn(dim, dim, |j, k| {
|
||||||
let n = j*dim + k;
|
let n = j*dim + k;
|
||||||
(E as f32)*((n*n) as f32) % 2.0_f32 - 1.0_f32
|
(E as f32)*((n*n) as f32) % 2.0_f32 - 1.0_f32
|
||||||
|
@ -79,6 +99,7 @@ pub fn rand_eigval_series(dim: usize, time_res: usize) -> Vec<OVector<Complex<f6
|
||||||
let n = j*dim + k;
|
let n = j*dim + k;
|
||||||
E*((n*n) as f64) % 2.0 - 1.0
|
E*((n*n) as f64) % 2.0 - 1.0
|
||||||
}) * (3.0 / (dim as f64)).sqrt();
|
}) * (3.0 / (dim as f64)).sqrt();
|
||||||
|
/*let mut rand_mat = OMatrix::<f64, N, N>::identity();*/
|
||||||
|
|
||||||
// initialize the rotation step
|
// initialize the rotation step
|
||||||
let mut rot_step = OMatrix::<f64, N, N>::identity();
|
let mut rot_step = OMatrix::<f64, N, N>::identity();
|
||||||
|
@ -101,4 +122,43 @@ pub fn rand_eigval_series(dim: usize, time_res: usize) -> Vec<OVector<Complex<f6
|
||||||
eigval_series.push(rand_mat.complex_eigenvalues());
|
eigval_series.push(rand_mat.complex_eigenvalues());
|
||||||
}
|
}
|
||||||
eigval_series
|
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
|
||||||
}*/
|
}*/
|
|
@ -1,3 +1,4 @@
|
||||||
|
use nalgebra::*;
|
||||||
use std::f64::consts::PI as PI;
|
use std::f64::consts::PI as PI;
|
||||||
use sycamore::{prelude::*, rt::{JsCast, JsValue}};
|
use sycamore::{prelude::*, rt::{JsCast, JsValue}};
|
||||||
use web_sys::window;
|
use web_sys::window;
|
||||||
|
@ -18,8 +19,7 @@ fn main() {
|
||||||
on_mount(move || {
|
on_mount(move || {
|
||||||
let performance = window().unwrap().performance().unwrap();
|
let performance = window().unwrap().performance().unwrap();
|
||||||
let start_time = performance.now();
|
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;
|
let run_time = performance.now() - start_time;
|
||||||
run_time_report.set(run_time);
|
run_time_report.set(run_time);
|
||||||
|
|
||||||
|
|
Loading…
Add table
Add a link
Reference in a new issue