forked from StudioInfinity/dyna3
Rust trial: write benchmark
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Aaron Fenyes
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6b0fad89dc
commit
0b3fe689cd
7 changed files with 345 additions and 0 deletions
176
lang-trials/rust-benchmark/src/engine.rs
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176
lang-trials/rust-benchmark/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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use web_sys::console;
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/*use std::ops::Sub;*/
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/*use typenum::{B1, UInt, UTerm};*/
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/*pub fn eigvals_rotated<N>(A: SMatrix<f64, N, N>, time: f64): complex_eigenvalues(&self) -> OVector<NumComplex<T>, D>*/
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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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console::log_1(&format!("dimension {dim}").into());
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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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console::log_1(&"before engine eigenvalues".into());
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eigval_series.push(rand_mat.complex_eigenvalues());
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console::log_1(&"after engine eigenvalues".into());
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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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/* another attempt at static matrices. i couldn't get the types to work out */
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/*pub fn random_eigval_series<const N: usize>(time_res: usize) -> Vec<OVector<Complex<f64>, Const<N>>>
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where
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Const<N>: ToTypenum,
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<Const<N> as ToTypenum>::Typenum: Sub<UInt<UTerm, B1>>,
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<<Const<N> as ToTypenum>::Typenum as Sub<UInt<UTerm, B1>>>::Output: ToConst
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{
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// initialize the random matrix
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/*let mut rand_mat = SMatrix::<f64, N, N>::zeros();
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for n in 0..N*N {
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rand_mat[n] = E*((n*n) as f64) % 2.0 - 1.0;
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}*/
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let rand_mat = OMatrix::<f64, Const<N>, Const<N>>::from_fn(|j, k| {
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let n = j*N + k;
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E*((n*n) as f64) % 2.0 - 1.0
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});
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// initialize the rotation step
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let mut rot_step = OMatrix::<f64, Const<N>, Const<N>>::identity();
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let max_freq = 4;
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for n in (0..N).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 eigvals = Vec::<OVector<Complex<f64>, Const<N>>>::with_capacity(time_res);
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unsafe { eigvals.set_len(time_res); }
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for t in 0..time_res {
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eigvals[t] = rand_mat.complex_eigenvalues();
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}
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eigvals
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}*/
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/* dynamic matrices */
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pub fn rand_eigval_series<N>(time_res: usize) -> Vec<OVector<Complex<f64>, Dyn>>
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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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console::log_1(&format!("dimension {dim}").into());
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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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console::log_1(&"before engine eigenvalues".into());
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eigval_series.push(rand_mat.complex_eigenvalues());
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console::log_1(&"after engine eigenvalues".into());
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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<N>(time_res: usize) -> Vec<OVector<Complex<f32>, Dyn>>
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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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console::log_1(&format!("dimension {dim}").into());
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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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console::log_1(&"before engine eigenvalues".into());
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eigval_series.push(rand_mat.complex_eigenvalues());
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console::log_1(&"after engine eigenvalues".into());
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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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86
lang-trials/rust-benchmark/src/main.rs
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86
lang-trials/rust-benchmark/src/main.rs
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@ -0,0 +1,86 @@
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use nalgebra::*;
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use std::f64::consts::PI as PI;
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use sycamore::{prelude::*, rt::{JsCast, JsValue}};
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use web_sys::{console, window};
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mod engine;
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fn main() {
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// set up a config option that forwards panic messages to `console.error`
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#[cfg(feature = "console_error_panic_hook")]
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console_error_panic_hook::set_once();
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/*console::log_1(&"before test schur 60".into());*/
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/*let test_rand_mat = OMatrix::<f64, U60, U60>::identity();*/
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/*let test_rot_step = OMatrix::<f64, U56, U56>::identity();*/
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/*let test_schur = test_rand_mat.schur();
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console::log_1(&format!("after test schur").into());
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let test_eigvals = test_schur.complex_eigenvalues();
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console::log_1(&format!("after test eigenvalues").into());*/
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sycamore::render(|| {
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let time_res: usize = 100;
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let time_step = create_signal(0.0);
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let run_time_report = create_signal(-1.0);
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let display = create_node_ref();
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on_mount(move || {
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let performance = window().unwrap().performance().unwrap();
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let start_time = performance.now();
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let eigval_series = engine::rand_eigval_series::<U60>(time_res);
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let run_time = performance.now() - start_time;
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run_time_report.set(run_time);
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let canvas = display
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.get::<DomNode>()
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.unchecked_into::<web_sys::HtmlCanvasElement>();
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let ctx = canvas
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.get_context("2d")
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.unwrap()
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.unwrap()
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.dyn_into::<web_sys::CanvasRenderingContext2d>()
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.unwrap();
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ctx.set_fill_style(&JsValue::from("white"));
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create_effect(move || {
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// center and normalize the coordinate system
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let width = canvas.width() as f64;
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let height = canvas.height() as f64;
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ctx.set_transform(1.0, 0.0, 0.0, -1.0, 0.5*width, 0.5*height).unwrap();
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// clear the previous frame
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ctx.clear_rect(-0.5*width, -0.5*width, width, height);
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// find the resolution
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const R_DISP: f64 = 1.5;
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let res = width / (2.0*R_DISP);
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// draw the eigenvalues
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let eigvals = &eigval_series[time_step.get() as usize];
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for n in 0..eigvals.len() {
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ctx.begin_path();
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ctx.arc(
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/* typecast only needed for single float version */
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res * f64::from(eigvals[n].re),
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res * f64::from(eigvals[n].im),
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3.0,
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0.0, 2.0*PI
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).unwrap();
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ctx.fill();
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}
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});
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});
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view! {
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div(id="app") {
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div { (run_time_report.get()) " ms" }
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canvas(ref=display, width="600", height="600")
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input(
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type="range",
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max=(time_res - 1).to_string(),
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bind:valueAsNumber=time_step
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)
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}
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}
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});
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}
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