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7 Commits

Author SHA1 Message Date
Aaron Fenyes
3665351e12 Scala benchmark: adjust interface code to match Rust 2024-08-09 15:19:48 -07:00
Aaron Fenyes
14fb6d01f0 Rust benchmark: tidy up a bit 2024-08-09 15:18:13 -07:00
Aaron Fenyes
0b3fe689cd Rust trial: write benchmark 2024-08-09 15:12:44 -07:00
Aaron Fenyes
6b0fad89dc Scala trial: write benchmark 2024-08-08 00:26:26 -07:00
Aaron Fenyes
0bd025dd14 Scala trial: clean up Laminar interface
Also, drop unused Breeze code in favor of Slash.
2024-08-07 13:40:09 -07:00
Aaron Fenyes
4f30f31686 Rust trial: Make git ignore Cargo.lock 2024-08-07 13:36:48 -07:00
Aaron Fenyes
c376fcdad8 Hack together a "Hello, world" in Scala with Laminar 2024-08-07 13:32:12 -07:00
22 changed files with 693 additions and 1 deletions

3
lang-trials/rust-benchmark/.gitignore vendored Normal file
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target/*
dist/*
Cargo.lock

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[package]
name = "sycamore-trial"
version = "0.1.0"
authors = ["Aaron"]
edition = "2021"
[features]
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
# all the `std::fmt` and `std::panicking` infrastructure, so isn't great for
# code size when deploying.
console_error_panic_hook = { version = "0.1.7", optional = true }
[dependencies.web-sys]
version = "0.3.69"
features = [
'CanvasRenderingContext2d',
'HtmlCanvasElement',
'Window',
'Performance'
]
[dev-dependencies]
wasm-bindgen-test = "0.3.34"
[profile.release]
opt-level = "s" # optimize for small code size
debug = true # include debug symbols

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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8"/>
<title>The circular law</title>
<link data-trunk rel="css" href="main.css"/>
</head>
<body></body>
</html>

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body {
margin-left: 20px;
margin-top: 20px;
color: #fcfcfc;
background-color: #202020;
}
#app {
display: flex;
flex-direction: column;
width: 600px;
}
canvas {
float: left;
background-color: #020202;
border-radius: 10px;
margin-top: 5px;
}
input {
margin-top: 5px;
}

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in profiling, most time is being spent in the `reflect` method:
f64:
sycamore_trial-3d0aca3efee8b5fd.wasm.nalgebra::geometry::reflection::Reflection<T,D,S>::reflect::h7899977a4ba0b1d3
sycamore_trial-3d0aca3efee8b5fd.wasm.nalgebra::geometry::reflection::Reflection<T,D,S>::reflect::hc337c3cb6e3b4061
sycamore_trial-3d0aca3efee8b5fd.wasm.nalgebra::geometry::reflection::Reflection<T,D,S>::reflect_rows::h43d0f6838d0c2833
f32:
sycamore_trial-3d0aca3efee8b5fd.wasm.nalgebra::geometry::reflection::Reflection<T,D,S>::reflect::h0e8ec322f198f847
sycamore_trial-3d0aca3efee8b5fd.wasm.nalgebra::geometry::reflection::Reflection<T,D,S>::reflect::h9928bdd5e72743ea
sycamore_trial-3d0aca3efee8b5fd.wasm.nalgebra::geometry::reflection::Reflection<T,D,S>::reflect_rows::h49f571fd8fc9b0f2
in one test, we spent 4000 ms in "WASM closure", but the enveloping "VoidFunction" takes 1300 ms longer. in another test, though, there's no overhang; the 7000 ms we spent in `rand_eigval_series` accounts for basically the entire load time, and matches the clock timing

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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>
{
// 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
}) * (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<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
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
}) * (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
}*/
/* 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
}*/

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use nalgebra::*;
use std::f64::consts::PI as PI;
use sycamore::{prelude::*, rt::{JsCast, JsValue}};
use web_sys::window;
mod engine;
fn main() {
// set up a config option that forwards panic messages to `console.error`
#[cfg(feature = "console_error_panic_hook")]
console_error_panic_hook::set_once();
sycamore::render(|| {
let time_res: usize = 100;
let time_step = create_signal(0.0);
let run_time_report = create_signal(-1.0);
let display = create_node_ref();
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 run_time = performance.now() - start_time;
run_time_report.set(run_time);
let canvas = display
.get::<DomNode>()
.unchecked_into::<web_sys::HtmlCanvasElement>();
let ctx = canvas
.get_context("2d")
.unwrap()
.unwrap()
.dyn_into::<web_sys::CanvasRenderingContext2d>()
.unwrap();
ctx.set_fill_style(&JsValue::from("white"));
create_effect(move || {
// center and normalize the coordinate system
let width = canvas.width() as f64;
let height = canvas.height() as f64;
ctx.set_transform(1.0, 0.0, 0.0, -1.0, 0.5*width, 0.5*height).unwrap();
// clear the previous frame
ctx.clear_rect(-0.5*width, -0.5*width, width, height);
// find the resolution
const R_DISP: f64 = 1.5;
let res = width / (2.0*R_DISP);
// draw the eigenvalues
let eigvals = &eigval_series[time_step.get() as usize];
for n in 0..eigvals.len() {
ctx.begin_path();
ctx.arc(
/* typecast only needed for single float version */
res * f64::from(eigvals[n].re),
res * f64::from(eigvals[n].im),
3.0,
0.0, 2.0*PI
).unwrap();
ctx.fill();
}
});
});
view! {
div(id="app") {
div { (run_time_report.get()) " ms" }
canvas(ref=display, width="600", height="600")
input(
type="range",
max=(time_res - 1).to_string(),
bind:valueAsNumber=time_step
)
}
}
});
}

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target/* target/*
dist/* dist/*
Cargo.lock

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target
sbt.json

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enablePlugins(ScalaJSPlugin)
name := "Circular Law"
scalaVersion := "3.4.2"
scalaJSUseMainModuleInitializer := true
libraryDependencies += "com.raquo" %%% "laminar" % "17.0.0"
libraryDependencies += "ai.dragonfly" %%% "slash" % "0.3.1"
libraryDependencies += "org.scala-js" %%% "scalajs-dom" % "2.8.0"

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<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>The circular law</title>
<script type="text/javascript" src="./target/scala-3.4.2/circular-law-fastopt/main.js"></script>
<link rel="stylesheet" href="main.css"/>
</head>
<body></body>
</html>

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body {
margin-left: 20px;
margin-top: 20px;
color: #fcfcfc;
background-color: #202020;
}
#app {
display: flex;
flex-direction: column;
width: 600px;
}
canvas {
float: left;
background-color: #020202;
border-radius: 10px;
margin-top: 5px;
}
input {
margin-top: 5px;
}

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sbt.version=1.10.1

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addSbtPlugin("org.scala-js" % "sbt-scalajs" % "1.16.0")

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import com.raquo.laminar.api.L.{*, given}
import narr.*
import org.scalajs.dom
import org.scalajs.dom.document
import scala.math.{cos, sin}
import slash.matrix.Matrix
import slash.matrix.decomposition.Eigen
object CircularLawApp:
val canvas = canvasTag(widthAttr := 600, heightAttr := 600)
val ctx = canvas.ref.getContext("2d").asInstanceOf[dom.CanvasRenderingContext2D]
val (eigvalSeries, runTimeReport) = randEigvalSeries[60]()
val timeStepState = Var("0")
def draw(timeStep: String): Unit =
// center and normalize the coordinate system
val width = canvas.ref.width
val height = canvas.ref.height
ctx.setTransform(1d, 0d, 0d, -1d, 0.5*width, 0.5*height)
// clear the previous frame
ctx.clearRect(-0.5*width, -0.5*width, width, height)
// find the resolution
val rDisp: Double = 1.5
val res = width / (2*rDisp)
// draw the eigenvalues
val eigvals = eigvalSeries(timeStep.toInt)
for n <- 0 to eigvals(0).length-1 do
ctx.beginPath()
ctx.arc(
res * eigvals(0)(n),
res * eigvals(1)(n),
3d,
0d, 2*math.Pi
)
ctx.fill()
def eigvalsRotated[N <: Int](A: Matrix[N, N], time: Double)(using ValueOf[N]): (NArray[Double], NArray[Double]) =
// create transformation
val maxFreq = 4
val T = Matrix.identity[N, N]
val dim: Int = valueOf[N]
for n <- 0 to dim by 2 do
val a = cos(math.Pi * time * (n % maxFreq))
val b = sin(math.Pi * time * (n % maxFreq))
T(n, n) = a
T(n+1, n) = b
T(n, n+1) = -b
T(n+1, n+1) = a
// find eigenvalues
val eigen = Eigen(T*A)
(
eigen.realEigenvalues.asInstanceOf[NArray[Double]],
eigen.imaginaryEigenvalues.asInstanceOf[NArray[Double]]
)
def randEigvalSeries[N <: Int]()(using ValueOf[N]): (List[(NArray[Double], NArray[Double])], String) =
val timeRes = 100
val dim: Int = valueOf[N]
val startTime = System.currentTimeMillis()
val A = new Matrix[N, N](
NArray.tabulate(dim*dim)(k => (math.E*k*k) % 2 - 1)
).times(math.sqrt(3d / dim))
val series = List.tabulate(timeRes)(t => eigvalsRotated(A, t.toDouble / timeRes))
val runTime = System.currentTimeMillis() - startTime
(series, runTime.toString() + " ms")
def main(args: Array[String]): Unit =
ctx.fillStyle = "white"
lazy val app = div(
idAttr := "app",
div(runTimeReport),
canvas,
input(
typ := "range",
maxAttr := (eigvalSeries.length-1).toString,
controlled(
value <-- timeStepState.signal,
onInput.mapToValue --> timeStepState.writer
),
timeStepState.signal --> draw
)
)
renderOnDomContentLoaded(document.body, app)

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lang-trials/scala/.gitignore vendored Normal file
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target
sbt.json

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enablePlugins(ScalaJSPlugin)
name := "Lattice Circle"
scalaVersion := "3.4.2"
// This is an application with a main method
scalaJSUseMainModuleInitializer := true
libraryDependencies += "com.raquo" %%% "laminar" % "17.0.0"
/*libraryDependencies += "org.scalanlp" %% "breeze" % "2.1.0"*/
libraryDependencies += "ai.dragonfly" %%% "slash" % "0.3.1"
libraryDependencies += "org.scala-js" %%% "scalajs-dom" % "2.8.0"

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<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>Lattice circle</title>
<script type="text/javascript" src="./target/scala-3.4.2/lattice-circle-fastopt/main.js"></script>
<link rel="stylesheet" href="main.css"/>
</head>
<body></body>
</html>

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body {
margin-left: 20px;
margin-top: 20px;
color: #fcfcfc;
background-color: #202020;
}
input {
color: inherit;
background-color: #020202;
border: 1px solid #606060;
min-width: 40px;
border-radius: 4px;
}
input.point-1 {
border-color: #ba5d09;
}
input.point-2 {
border-color: #0e8a06;
}
input.point-3 {
border-color: #8951fb;
}
#data-panel {
float: left;
margin-left: 20px;
display: grid;
grid-template-columns: auto auto;
gap: 10px 10px;
width: 120px;
}
#data-panel > div {
text-align: center;
}
canvas {
float: left;
background-color: #020202;
border-radius: 10px;
}

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sbt.version=1.10.1

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addSbtPlugin("org.scala-js" % "sbt-scalajs" % "1.16.0")

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// based on the Laminar example app
//
// https://github.com/raquo/laminar-examples/blob/master/src/main/scala/App.scala
//
// and Li Haoyi's example canvas app
//
// http://www.lihaoyi.com/hands-on-scala-js/#MakingaCanvasApp
//
import com.raquo.laminar.api.L.{*, given}
import narr.*
import org.scalajs.dom
import org.scalajs.dom.document
import scala.math
import slash.matrix.*
class Circle(var centerX: Double, var centerY: Double, var radius: Double)
object LatticeCircleApp:
val canvas = canvasTag(widthAttr := 600, heightAttr := 600)
val ctx = canvas.ref.getContext("2d").asInstanceOf[dom.CanvasRenderingContext2D]
val data = List("-1", "0", "0", "-1", "1", "0").map(Var(_))
def circThru(points: Matrix[3, 2]): Option[Circle] =
// build the matrix that maps the circle's coefficient vector to the
// negative of the linear part of the circle's equation, evaluated at the
// given points
val negLinPart = Matrix.ones[3, 3]
negLinPart.setMatrix(0, 0, points * 2.0)
// find the quadrdatic part of the circle's equation, evaluated at the given
// points
val quadPart = Matrix[3, 1](
NArray.tabulate[Double](3)(
k => points(k, 0)*points(k, 0) + points(k, 1)*points(k, 1)
)
)
// find the circle's coefficient vector, and from there its center and
// radius
try
val coeffs = negLinPart.solve(quadPart)
val centerX = coeffs(0, 0)
val centerY = coeffs(1, 0)
Some(Circle(
centerX,
centerY,
math.sqrt(coeffs(2, 0) + centerX*centerX + centerY*centerY)
))
catch
_ => return None
def draw(): Unit =
// center and normalize the coordinate system
val width = canvas.ref.width
val height = canvas.ref.height
ctx.setTransform(1.0, 0.0, 0.0, -1.0, 0.5*width, 0.5*height)
// clear the previous frame
ctx.clearRect(-0.5*width, -0.5*width, width, height)
// find the resolution
val rDisp = 5.0
val res = width / (2.0*rDisp)
// set colors
val highlightStyle = "white"
val gridStyle = "#404040"
val pointFillStyles = List("#ba5d09", "#0e8a06", "#8951fb")
val pointStrokeStyles = List("#f89142", "#58c145", "#c396fc")
// draw the grid
val rGrid = (rDisp - 0.01).floor.toInt
val edgeScr = res * rDisp
ctx.strokeStyle = gridStyle
for t <- -rGrid to rGrid do
val tScr = res * t
// draw horizontal grid line
ctx.beginPath();
ctx.moveTo(-edgeScr, tScr)
ctx.lineTo(edgeScr, tScr)
ctx.stroke()
// draw vertical grid line
ctx.beginPath();
ctx.moveTo(tScr, -edgeScr)
ctx.lineTo(tScr, edgeScr)
ctx.stroke()
// find and draw the circle through the given points
val dataNow = NArray.tabulate(6)(n =>
try
data(n).signal.now().toDouble
catch
_ => Double.NaN
)
if dataNow.forall(t => t == t.floor) then
// all of the coordinates are integer and non-NaN
val points = Matrix[3, 2](dataNow)
circThru(points) match
case Some(circ) =>
ctx.beginPath()
ctx.strokeStyle = highlightStyle
ctx.arc(
res * circ.centerX,
res * circ.centerY,
res * circ.radius,
0.0, 2.0*math.Pi
)
ctx.stroke()
case None =>
// draw the data points
for n <- 0 to 2 do
val indX = 2*n
val indY = indX + 1
if
dataNow(indX) == dataNow(indX).floor &&
dataNow(indY) == dataNow(indY).floor
then
ctx.beginPath()
ctx.fillStyle = pointFillStyles(n)
ctx.strokeStyle = pointStrokeStyles(n)
ctx.arc(
res * dataNow(indX),
res * dataNow(indY),
3.0,
0.0, 2.0*math.Pi
)
ctx.fill()
ctx.stroke()
def coordInput(n: Int): Input =
input(
typ := "number",
cls := s"point-${(1.0 + 0.5*n).floor.toInt}",
controlled(
value <-- data(n).signal,
onInput.mapToValue --> data(n).writer
),
data(n).signal --> { _ => draw() }
)
def main(args: Array[String]): Unit =
lazy val app = div(
canvas,
div(
idAttr := "data-panel",
div("x"),
div("y"),
coordInput(0),
coordInput(1),
coordInput(2),
coordInput(3),
coordInput(4),
coordInput(5)
)
)
renderOnDomContentLoaded(document.body, app)