WIP: Clean up the outline view #16
@ -1,7 +1,7 @@
|
||||
[package]
|
||||
name = "sketch-outline"
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name = "dyna3"
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version = "0.1.0"
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authors = ["Aaron"]
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authors = ["Aaron Fenyes", "Glen Whitney"]
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edition = "2021"
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[features]
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@ -10,6 +10,7 @@ default = ["console_error_panic_hook"]
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[dependencies]
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itertools = "0.13.0"
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js-sys = "0.3.70"
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lazy_static = "1.5.0"
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||||
nalgebra = "0.33.0"
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rustc-hash = "2.0.0"
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slab = "0.4.9"
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@ -25,6 +26,7 @@ console_error_panic_hook = { version = "0.1.7", optional = true }
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version = "0.3.69"
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features = [
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'HtmlCanvasElement',
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'HtmlInputElement',
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'Performance',
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'WebGl2RenderingContext',
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'WebGlBuffer',
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@ -2,8 +2,10 @@
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<html>
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<head>
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<meta charset="utf-8"/>
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<title>Sketch outline</title>
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<title>dyna3</title>
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<link data-trunk rel="css" href="main.css"/>
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<link href="https://fonts.bunny.net/css?family=fira-sans:ital,wght@0,400;1,400&display=swap" rel="stylesheet">
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<link href="https://fonts.bunny.net/css?family=noto-emoji:wght@400&text=%f0%9f%94%97%e2%9a%a0&display=swap" rel="stylesheet">
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</head>
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<body></body>
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</html>
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@ -2,6 +2,7 @@ body {
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margin: 0px;
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color: #fcfcfc;
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background-color: #222;
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font-family: 'Fira Sans', sans-serif;
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}
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/* sidebar */
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@ -33,6 +34,11 @@ body {
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font-size: large;
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}
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/* KLUDGE */
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#add-remove > button.emoji {
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font-family: 'Noto Emoji', sans-serif;
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}
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/* outline */
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#outline {
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@ -93,10 +99,11 @@ details[open]:has(li) .elt-switch::after {
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display: flex;
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}
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.elt-rep > div, .cst-rep {
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.elt-rep > div {
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padding: 2px 0px 0px 0px;
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font-size: 10pt;
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text-align: center;
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font-variant-numeric: tabular-nums;
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text-align: right;
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width: 56px;
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}
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@ -104,10 +111,38 @@ details[open]:has(li) .elt-switch::after {
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font-style: italic;
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}
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.cst > input {
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.cst.invalid {
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color: #f58fc2;
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}
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.cst > input[type=checkbox] {
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margin: 0px 8px 0px 0px;
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}
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.cst > input[type=text] {
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color: inherit;
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background-color: inherit;
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border: 1px solid #555;
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border-radius: 2px;
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}
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.cst.invalid > input[type=text] {
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border-color: #70495c;
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}
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.status {
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width: 20px;
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padding-left: 4px;
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text-align: center;
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font-family: 'Noto Emoji';
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font-style: normal;
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}
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.invalid > .status::after, details:has(.invalid):not([open]) .status::after {
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content: '⚠';
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color: #f58fc2;
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}
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/* display */
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canvas {
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8
app-proto/run-examples
Executable file
8
app-proto/run-examples
Executable file
@ -0,0 +1,8 @@
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# based on "Enabling print statements in Cargo tests", by Jon Almeida
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#
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# https://jonalmeida.com/posts/2015/01/23/print-cargo/
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#
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cargo test -- --nocapture engine::tests::irisawa_hexlet_test
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cargo test -- --nocapture engine::tests::three_spheres_example
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cargo test -- --nocapture engine::tests::point_on_sphere_example
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@ -1,4 +1,3 @@
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use std::collections::BTreeSet; /* DEBUG */
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use sycamore::prelude::*;
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use web_sys::{console, wasm_bindgen::JsValue};
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@ -7,68 +6,52 @@ use crate::{engine, AppState, assembly::{Assembly, Constraint, Element}};
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/* DEBUG */
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fn load_gen_assemb(assembly: &Assembly) {
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let _ = assembly.try_insert_element(
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Element {
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id: String::from("gemini_a"),
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label: String::from("Castor"),
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color: [1.00_f32, 0.25_f32, 0.00_f32],
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rep: engine::sphere(0.5, 0.5, 0.0, 1.0),
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constraints: BTreeSet::default()
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}
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Element::new(
|
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String::from("gemini_a"),
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String::from("Castor"),
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[1.00_f32, 0.25_f32, 0.00_f32],
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engine::sphere(0.5, 0.5, 0.0, 1.0)
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)
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);
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let _ = assembly.try_insert_element(
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Element {
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id: String::from("gemini_b"),
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label: String::from("Pollux"),
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color: [0.00_f32, 0.25_f32, 1.00_f32],
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rep: engine::sphere(-0.5, -0.5, 0.0, 1.0),
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constraints: BTreeSet::default()
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}
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Element::new(
|
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String::from("gemini_b"),
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String::from("Pollux"),
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[0.00_f32, 0.25_f32, 1.00_f32],
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engine::sphere(-0.5, -0.5, 0.0, 1.0)
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)
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);
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let _ = assembly.try_insert_element(
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Element {
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id: String::from("ursa_major"),
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label: String::from("Ursa major"),
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color: [0.25_f32, 0.00_f32, 1.00_f32],
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rep: engine::sphere(-0.5, 0.5, 0.0, 0.75),
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constraints: BTreeSet::default()
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}
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Element::new(
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String::from("ursa_major"),
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String::from("Ursa major"),
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[0.25_f32, 0.00_f32, 1.00_f32],
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engine::sphere(-0.5, 0.5, 0.0, 0.75)
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)
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);
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let _ = assembly.try_insert_element(
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Element {
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id: String::from("ursa_minor"),
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label: String::from("Ursa minor"),
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color: [0.25_f32, 1.00_f32, 0.00_f32],
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rep: engine::sphere(0.5, -0.5, 0.0, 0.5),
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constraints: BTreeSet::default()
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||||
}
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Element::new(
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String::from("ursa_minor"),
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String::from("Ursa minor"),
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[0.25_f32, 1.00_f32, 0.00_f32],
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engine::sphere(0.5, -0.5, 0.0, 0.5)
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)
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);
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let _ = assembly.try_insert_element(
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Element {
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id: String::from("moon_deimos"),
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label: String::from("Deimos"),
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color: [0.75_f32, 0.75_f32, 0.00_f32],
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rep: engine::sphere(0.0, 0.15, 1.0, 0.25),
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constraints: BTreeSet::default()
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||||
}
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Element::new(
|
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String::from("moon_deimos"),
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String::from("Deimos"),
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[0.75_f32, 0.75_f32, 0.00_f32],
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engine::sphere(0.0, 0.15, 1.0, 0.25)
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)
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);
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let _ = assembly.try_insert_element(
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Element {
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id: String::from("moon_phobos"),
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label: String::from("Phobos"),
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color: [0.00_f32, 0.75_f32, 0.50_f32],
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rep: engine::sphere(0.0, -0.15, -1.0, 0.25),
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constraints: BTreeSet::default()
|
||||
}
|
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);
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assembly.insert_constraint(
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Constraint {
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args: (
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assembly.elements_by_id.with_untracked(|elts_by_id| elts_by_id["gemini_a"]),
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assembly.elements_by_id.with_untracked(|elts_by_id| elts_by_id["gemini_b"])
|
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),
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rep: 0.5,
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active: create_signal(true)
|
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}
|
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Element::new(
|
||||
String::from("moon_phobos"),
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String::from("Phobos"),
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[0.00_f32, 0.75_f32, 0.50_f32],
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engine::sphere(0.0, -0.15, -1.0, 0.25)
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)
|
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);
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}
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@ -76,76 +59,68 @@ fn load_gen_assemb(assembly: &Assembly) {
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fn load_low_curv_assemb(assembly: &Assembly) {
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let a = 0.75_f64.sqrt();
|
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let _ = assembly.try_insert_element(
|
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Element {
|
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id: "central".to_string(),
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label: "Central".to_string(),
|
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color: [0.75_f32, 0.75_f32, 0.75_f32],
|
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rep: engine::sphere(0.0, 0.0, 0.0, 1.0),
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constraints: BTreeSet::default()
|
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}
|
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Element::new(
|
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"central".to_string(),
|
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"Central".to_string(),
|
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[0.75_f32, 0.75_f32, 0.75_f32],
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engine::sphere(0.0, 0.0, 0.0, 1.0)
|
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)
|
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);
|
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let _ = assembly.try_insert_element(
|
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Element {
|
||||
id: "assemb_plane".to_string(),
|
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label: "Assembly plane".to_string(),
|
||||
color: [0.75_f32, 0.75_f32, 0.75_f32],
|
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rep: engine::sphere_with_offset(0.0, 0.0, 1.0, 0.0, 0.0),
|
||||
constraints: BTreeSet::default()
|
||||
}
|
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Element::new(
|
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"assemb_plane".to_string(),
|
||||
"Assembly plane".to_string(),
|
||||
[0.75_f32, 0.75_f32, 0.75_f32],
|
||||
engine::sphere_with_offset(0.0, 0.0, 1.0, 0.0, 0.0)
|
||||
)
|
||||
);
|
||||
let _ = assembly.try_insert_element(
|
||||
Element {
|
||||
id: "side1".to_string(),
|
||||
label: "Side 1".to_string(),
|
||||
color: [1.00_f32, 0.00_f32, 0.25_f32],
|
||||
rep: engine::sphere_with_offset(1.0, 0.0, 0.0, 1.0, 0.0),
|
||||
constraints: BTreeSet::default()
|
||||
}
|
||||
Element::new(
|
||||
"side1".to_string(),
|
||||
"Side 1".to_string(),
|
||||
[1.00_f32, 0.00_f32, 0.25_f32],
|
||||
engine::sphere_with_offset(1.0, 0.0, 0.0, 1.0, 0.0)
|
||||
)
|
||||
);
|
||||
let _ = assembly.try_insert_element(
|
||||
Element {
|
||||
id: "side2".to_string(),
|
||||
label: "Side 2".to_string(),
|
||||
color: [0.25_f32, 1.00_f32, 0.00_f32],
|
||||
rep: engine::sphere_with_offset(-0.5, a, 0.0, 1.0, 0.0),
|
||||
constraints: BTreeSet::default()
|
||||
}
|
||||
Element::new(
|
||||
"side2".to_string(),
|
||||
"Side 2".to_string(),
|
||||
[0.25_f32, 1.00_f32, 0.00_f32],
|
||||
engine::sphere_with_offset(-0.5, a, 0.0, 1.0, 0.0)
|
||||
)
|
||||
);
|
||||
let _ = assembly.try_insert_element(
|
||||
Element {
|
||||
id: "side3".to_string(),
|
||||
label: "Side 3".to_string(),
|
||||
color: [0.00_f32, 0.25_f32, 1.00_f32],
|
||||
rep: engine::sphere_with_offset(-0.5, -a, 0.0, 1.0, 0.0),
|
||||
constraints: BTreeSet::default()
|
||||
}
|
||||
Element::new(
|
||||
"side3".to_string(),
|
||||
"Side 3".to_string(),
|
||||
[0.00_f32, 0.25_f32, 1.00_f32],
|
||||
engine::sphere_with_offset(-0.5, -a, 0.0, 1.0, 0.0)
|
||||
)
|
||||
);
|
||||
let _ = assembly.try_insert_element(
|
||||
Element {
|
||||
id: "corner1".to_string(),
|
||||
label: "Corner 1".to_string(),
|
||||
color: [0.75_f32, 0.75_f32, 0.75_f32],
|
||||
rep: engine::sphere(-4.0/3.0, 0.0, 0.0, 1.0/3.0),
|
||||
constraints: BTreeSet::default()
|
||||
}
|
||||
Element::new(
|
||||
"corner1".to_string(),
|
||||
"Corner 1".to_string(),
|
||||
[0.75_f32, 0.75_f32, 0.75_f32],
|
||||
engine::sphere(-4.0/3.0, 0.0, 0.0, 1.0/3.0)
|
||||
)
|
||||
);
|
||||
let _ = assembly.try_insert_element(
|
||||
Element {
|
||||
id: "corner2".to_string(),
|
||||
label: "Corner 2".to_string(),
|
||||
color: [0.75_f32, 0.75_f32, 0.75_f32],
|
||||
rep: engine::sphere(2.0/3.0, -4.0/3.0 * a, 0.0, 1.0/3.0),
|
||||
constraints: BTreeSet::default()
|
||||
}
|
||||
Element::new(
|
||||
"corner2".to_string(),
|
||||
"Corner 2".to_string(),
|
||||
[0.75_f32, 0.75_f32, 0.75_f32],
|
||||
engine::sphere(2.0/3.0, -4.0/3.0 * a, 0.0, 1.0/3.0)
|
||||
)
|
||||
);
|
||||
let _ = assembly.try_insert_element(
|
||||
Element {
|
||||
id: String::from("corner3"),
|
||||
label: String::from("Corner 3"),
|
||||
color: [0.75_f32, 0.75_f32, 0.75_f32],
|
||||
rep: engine::sphere(2.0/3.0, 4.0/3.0 * a, 0.0, 1.0/3.0),
|
||||
constraints: BTreeSet::default()
|
||||
}
|
||||
Element::new(
|
||||
String::from("corner3"),
|
||||
String::from("Corner 3"),
|
||||
[0.75_f32, 0.75_f32, 0.75_f32],
|
||||
engine::sphere(2.0/3.0, 4.0/3.0 * a, 0.0, 1.0/3.0)
|
||||
)
|
||||
);
|
||||
}
|
||||
|
||||
@ -198,6 +173,7 @@ pub fn AddRemove() -> View {
|
||||
}
|
||||
) { "+" }
|
||||
button(
|
||||
class="emoji", /* KLUDGE */
|
||||
disabled={
|
||||
let state = use_context::<AppState>();
|
||||
state.selection.with(|sel| sel.len() != 2)
|
||||
@ -210,16 +186,21 @@ pub fn AddRemove() -> View {
|
||||
(arg_vec[0].clone(), arg_vec[1].clone())
|
||||
}
|
||||
);
|
||||
let rep = create_signal(0.0);
|
||||
let rep_valid = create_signal(false);
|
||||
let active = create_signal(true);
|
||||
state.assembly.insert_constraint(Constraint {
|
||||
args: args,
|
||||
rep: 0.0,
|
||||
active: create_signal(true)
|
||||
rep: rep,
|
||||
rep_text: create_signal(String::new()),
|
||||
rep_valid: rep_valid,
|
||||
active: active,
|
||||
});
|
||||
state.selection.update(|sel| sel.clear());
|
||||
|
||||
/* DEBUG */
|
||||
// print updated constraint list
|
||||
console::log_1(&JsValue::from("constraints:"));
|
||||
console::log_1(&JsValue::from("Constraints:"));
|
||||
state.assembly.constraints.with(|csts| {
|
||||
for (_, cst) in csts.into_iter() {
|
||||
console::log_5(
|
||||
@ -227,10 +208,22 @@ pub fn AddRemove() -> View {
|
||||
&JsValue::from(cst.args.0),
|
||||
&JsValue::from(cst.args.1),
|
||||
&JsValue::from(":"),
|
||||
&JsValue::from(cst.rep)
|
||||
&JsValue::from(cst.rep.get_untracked())
|
||||
);
|
||||
}
|
||||
});
|
||||
|
||||
// update the realization when the constraint becomes active
|
||||
// and valid, or is edited while active and valid
|
||||
create_effect(move || {
|
||||
console::log_1(&JsValue::from(
|
||||
format!("Constraint ({}, {}) updated", args.0, args.1)
|
||||
));
|
||||
rep.track();
|
||||
if active.get() && rep_valid.get() {
|
||||
state.assembly.realize();
|
||||
}
|
||||
});
|
||||
}
|
||||
) { "🔗" }
|
||||
select(bind:value=assembly_name) { /* DEBUG */
|
||||
|
||||
@ -1,22 +1,49 @@
|
||||
use nalgebra::DVector;
|
||||
use nalgebra::{DMatrix, DVector};
|
||||
use rustc_hash::FxHashMap;
|
||||
use slab::Slab;
|
||||
use std::collections::BTreeSet;
|
||||
use sycamore::prelude::*;
|
||||
use web_sys::{console, wasm_bindgen::JsValue}; /* DEBUG */
|
||||
|
||||
use crate::engine::{realize_gram, PartialMatrix};
|
||||
|
||||
#[derive(Clone, PartialEq)]
|
||||
pub struct Element {
|
||||
pub id: String,
|
||||
pub label: String,
|
||||
pub color: [f32; 3],
|
||||
pub rep: DVector<f64>,
|
||||
pub constraints: BTreeSet<usize>
|
||||
pub rep: Signal<DVector<f64>>,
|
||||
pub constraints: Signal<BTreeSet<usize>>,
|
||||
|
||||
// internal properties, not reflected in any view
|
||||
pub index: usize
|
||||
}
|
||||
|
||||
impl Element {
|
||||
pub fn new(
|
||||
id: String,
|
||||
label: String,
|
||||
color: [f32; 3],
|
||||
rep: DVector<f64>
|
||||
) -> Element {
|
||||
Element {
|
||||
id: id,
|
||||
label: label,
|
||||
color: color,
|
||||
rep: create_signal(rep),
|
||||
constraints: create_signal(BTreeSet::default()),
|
||||
index: 0
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
#[derive(Clone)]
|
||||
pub struct Constraint {
|
||||
pub args: (usize, usize),
|
||||
pub rep: f64,
|
||||
pub rep: Signal<f64>,
|
||||
pub rep_text: Signal<String>,
|
||||
pub rep_valid: Signal<bool>,
|
||||
pub active: Signal<bool>
|
||||
}
|
||||
|
||||
@ -40,6 +67,8 @@ impl Assembly {
|
||||
}
|
||||
}
|
||||
|
||||
// --- inserting elements and constraints ---
|
||||
|
||||
// insert an element into the assembly without checking whether we already
|
||||
// have an element with the same identifier. any element that does have the
|
||||
// same identifier will get kicked out of the `elements_by_id` index
|
||||
@ -72,22 +101,103 @@ impl Assembly {
|
||||
|
||||
// create and insert a new element
|
||||
self.insert_element_unchecked(
|
||||
Element {
|
||||
id: id,
|
||||
label: format!("Sphere {}", id_num),
|
||||
color: [0.75_f32, 0.75_f32, 0.75_f32],
|
||||
rep: DVector::<f64>::from_column_slice(&[0.0, 0.0, 0.0, 0.5, -0.5]),
|
||||
constraints: BTreeSet::default()
|
||||
}
|
||||
Element::new(
|
||||
id,
|
||||
format!("Sphere {}", id_num),
|
||||
[0.75_f32, 0.75_f32, 0.75_f32],
|
||||
DVector::<f64>::from_column_slice(&[0.0, 0.0, 0.0, 0.5, -0.5])
|
||||
)
|
||||
);
|
||||
}
|
||||
|
||||
pub fn insert_constraint(&self, constraint: Constraint) {
|
||||
let args = constraint.args;
|
||||
let key = self.constraints.update(|csts| csts.insert(constraint));
|
||||
self.elements.update(|elts| {
|
||||
elts[args.0].constraints.insert(key);
|
||||
elts[args.1].constraints.insert(key);
|
||||
})
|
||||
let arg_constraints = self.elements.with(
|
||||
|elts| (elts[args.0].constraints, elts[args.1].constraints)
|
||||
);
|
||||
arg_constraints.0.update(|csts| csts.insert(key));
|
||||
arg_constraints.1.update(|csts| csts.insert(key));
|
||||
}
|
||||
|
||||
// --- realization ---
|
||||
|
||||
pub fn realize(&self) {
|
||||
// index the elements
|
||||
self.elements.update_silent(|elts| {
|
||||
for (index, (_, elt)) in elts.into_iter().enumerate() {
|
||||
elt.index = index;
|
||||
}
|
||||
});
|
||||
|
||||
// set up the Gram matrix and the initial configuration matrix
|
||||
let (gram, guess) = self.elements.with_untracked(|elts| {
|
||||
// set up the off-diagonal part of the Gram matrix
|
||||
let mut gram_to_be = PartialMatrix::new();
|
||||
self.constraints.with_untracked(|csts| {
|
||||
for (_, cst) in csts {
|
||||
if cst.active.get_untracked() && cst.rep_valid.get_untracked() {
|
||||
let args = cst.args;
|
||||
let row = elts[args.0].index;
|
||||
let col = elts[args.1].index;
|
||||
gram_to_be.push_sym(row, col, cst.rep.get_untracked());
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
// set up the initial configuration matrix and the diagonal of the
|
||||
// Gram matrix
|
||||
let mut guess_to_be = DMatrix::<f64>::zeros(5, elts.len());
|
||||
for (_, elt) in elts {
|
||||
let index = elt.index;
|
||||
gram_to_be.push_sym(index, index, 1.0);
|
||||
guess_to_be.set_column(index, &elt.rep.get_clone_untracked());
|
||||
}
|
||||
|
||||
(gram_to_be, guess_to_be)
|
||||
});
|
||||
|
||||
/* DEBUG */
|
||||
// log the Gram matrix
|
||||
console::log_1(&JsValue::from("Gram matrix:"));
|
||||
gram.log_to_console();
|
||||
|
||||
/* DEBUG */
|
||||
// log the initial configuration matrix
|
||||
console::log_1(&JsValue::from("Old configuration:"));
|
||||
for j in 0..guess.nrows() {
|
||||
let mut row_str = String::new();
|
||||
for k in 0..guess.ncols() {
|
||||
row_str.push_str(format!(" {:>8.3}", guess[(j, k)]).as_str());
|
||||
}
|
||||
console::log_1(&JsValue::from(row_str));
|
||||
}
|
||||
|
||||
// look for a configuration with the given Gram matrix
|
||||
let (config, success, history) = realize_gram(
|
||||
&gram, guess, &[],
|
||||
1.0e-12, 0.5, 0.9, 1.1, 200, 110
|
||||
);
|
||||
|
||||
/* DEBUG */
|
||||
// report the outcome of the search
|
||||
console::log_1(&JsValue::from(
|
||||
if success {
|
||||
"Target accuracy achieved!"
|
||||
} else {
|
||||
"Failed to reach target accuracy"
|
||||
}
|
||||
));
|
||||
console::log_2(&JsValue::from("Steps:"), &JsValue::from(history.scaled_loss.len() - 1));
|
||||
console::log_2(&JsValue::from("Loss:"), &JsValue::from(*history.scaled_loss.last().unwrap()));
|
||||
|
||||
if success {
|
||||
// read out the solution
|
||||
for (_, elt) in self.elements.get_clone_untracked() {
|
||||
elt.rep.update(
|
||||
|rep| rep.set_column(0, &config.column(elt.index))
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -103,7 +103,11 @@ pub fn Display() -> View {
|
||||
// change listener
|
||||
let scene_changed = create_signal(true);
|
||||
create_effect(move || {
|
||||
state.assembly.elements.track();
|
||||
state.assembly.elements.with(|elts| {
|
||||
for (_, elt) in elts {
|
||||
elt.rep.track();
|
||||
}
|
||||
});
|
||||
state.selection.track();
|
||||
scene_changed.set(true);
|
||||
});
|
||||
@ -295,23 +299,40 @@ pub fn Display() -> View {
|
||||
let assembly_to_world = &location * &orientation;
|
||||
|
||||
// get the assembly
|
||||
let elements = state.assembly.elements.get_clone();
|
||||
let element_iter = (&elements).into_iter();
|
||||
let reps_world: Vec<_> = element_iter.clone().map(|(_, elt)| &assembly_to_world * &elt.rep).collect();
|
||||
let colors: Vec<_> = element_iter.clone().map(|(key, elt)|
|
||||
if state.selection.with(|sel| sel.contains(&key)) {
|
||||
elt.color.map(|ch| 0.2 + 0.8*ch)
|
||||
} else {
|
||||
elt.color
|
||||
}
|
||||
).collect();
|
||||
let highlights: Vec<_> = element_iter.map(|(key, _)|
|
||||
if state.selection.with(|sel| sel.contains(&key)) {
|
||||
1.0_f32
|
||||
} else {
|
||||
HIGHLIGHT
|
||||
}
|
||||
).collect();
|
||||
let (
|
||||
elt_cnt,
|
||||
reps_world,
|
||||
colors,
|
||||
highlights
|
||||
) = state.assembly.elements.with(|elts| {
|
||||
(
|
||||
// number of elements
|
||||
elts.len() as i32,
|
||||
|
||||
// representation vectors in world coordinates
|
||||
elts.iter().map(
|
||||
|(_, elt)| elt.rep.with(|rep| &assembly_to_world * rep)
|
||||
).collect::<Vec<_>>(),
|
||||
|
||||
// colors
|
||||
elts.iter().map(|(key, elt)| {
|
||||
if state.selection.with(|sel| sel.contains(&key)) {
|
||||
elt.color.map(|ch| 0.2 + 0.8*ch)
|
||||
} else {
|
||||
elt.color
|
||||
}
|
||||
}).collect::<Vec<_>>(),
|
||||
|
||||
// highlight levels
|
||||
elts.iter().map(|(key, _)| {
|
||||
if state.selection.with(|sel| sel.contains(&key)) {
|
||||
1.0_f32
|
||||
} else {
|
||||
HIGHLIGHT
|
||||
}
|
||||
}).collect::<Vec<_>>()
|
||||
)
|
||||
});
|
||||
|
||||
// set the resolution
|
||||
let width = canvas.width() as f32;
|
||||
@ -320,7 +341,7 @@ pub fn Display() -> View {
|
||||
ctx.uniform1f(shortdim_loc.as_ref(), width.min(height));
|
||||
|
||||
// pass the assembly
|
||||
ctx.uniform1i(sphere_cnt_loc.as_ref(), elements.len() as i32);
|
||||
ctx.uniform1i(sphere_cnt_loc.as_ref(), elt_cnt);
|
||||
for n in 0..reps_world.len() {
|
||||
let v = &reps_world[n];
|
||||
ctx.uniform3f(
|
||||
|
||||
@ -1,4 +1,12 @@
|
||||
use nalgebra::DVector;
|
||||
use lazy_static::lazy_static;
|
||||
use nalgebra::{Const, DMatrix, DVector, Dyn};
|
||||
use web_sys::{console, wasm_bindgen::JsValue}; /* DEBUG */
|
||||
|
||||
// --- elements ---
|
||||
|
||||
pub fn point(x: f64, y: f64, z: f64) -> DVector<f64> {
|
||||
DVector::from_column_slice(&[x, y, z, 0.5, 0.5*(x*x + y*y + z*z)])
|
||||
}
|
||||
|
||||
// the sphere with the given center and radius, with inward-pointing normals
|
||||
pub fn sphere(center_x: f64, center_y: f64, center_z: f64, radius: f64) -> DVector<f64> {
|
||||
@ -25,3 +33,470 @@ pub fn sphere_with_offset(dir_x: f64, dir_y: f64, dir_z: f64, off: f64, curv: f6
|
||||
off * (1.0 + 0.5 * off * curv)
|
||||
])
|
||||
}
|
||||
|
||||
// --- partial matrices ---
|
||||
|
||||
struct MatrixEntry {
|
||||
index: (usize, usize),
|
||||
value: f64
|
||||
}
|
||||
|
||||
pub struct PartialMatrix(Vec<MatrixEntry>);
|
||||
|
||||
impl PartialMatrix {
|
||||
pub fn new() -> PartialMatrix {
|
||||
PartialMatrix(Vec::<MatrixEntry>::new())
|
||||
}
|
||||
|
||||
pub fn push_sym(&mut self, row: usize, col: usize, value: f64) {
|
||||
let PartialMatrix(entries) = self;
|
||||
entries.push(MatrixEntry { index: (row, col), value: value });
|
||||
if row != col {
|
||||
entries.push(MatrixEntry { index: (col, row), value: value });
|
||||
}
|
||||
}
|
||||
|
||||
/* DEBUG */
|
||||
pub fn log_to_console(&self) {
|
||||
let PartialMatrix(entries) = self;
|
||||
for ent in entries {
|
||||
let ent_str = format!(" {} {} {}", ent.index.0, ent.index.1, ent.value);
|
||||
console::log_1(&JsValue::from(ent_str.as_str()));
|
||||
}
|
||||
}
|
||||
|
||||
fn proj(&self, a: &DMatrix<f64>) -> DMatrix<f64> {
|
||||
let mut result = DMatrix::<f64>::zeros(a.nrows(), a.ncols());
|
||||
let PartialMatrix(entries) = self;
|
||||
for ent in entries {
|
||||
result[ent.index] = a[ent.index];
|
||||
}
|
||||
result
|
||||
}
|
||||
|
||||
fn sub_proj(&self, rhs: &DMatrix<f64>) -> DMatrix<f64> {
|
||||
let mut result = DMatrix::<f64>::zeros(rhs.nrows(), rhs.ncols());
|
||||
let PartialMatrix(entries) = self;
|
||||
for ent in entries {
|
||||
result[ent.index] = ent.value - rhs[ent.index];
|
||||
}
|
||||
result
|
||||
}
|
||||
}
|
||||
|
||||
// --- descent history ---
|
||||
|
||||
pub struct DescentHistory {
|
||||
pub config: Vec<DMatrix<f64>>,
|
||||
pub scaled_loss: Vec<f64>,
|
||||
pub neg_grad: Vec<DMatrix<f64>>,
|
||||
pub min_eigval: Vec<f64>,
|
||||
pub base_step: Vec<DMatrix<f64>>,
|
||||
pub backoff_steps: Vec<i32>
|
||||
}
|
||||
|
||||
impl DescentHistory {
|
||||
fn new() -> DescentHistory {
|
||||
DescentHistory {
|
||||
config: Vec::<DMatrix<f64>>::new(),
|
||||
scaled_loss: Vec::<f64>::new(),
|
||||
neg_grad: Vec::<DMatrix<f64>>::new(),
|
||||
min_eigval: Vec::<f64>::new(),
|
||||
base_step: Vec::<DMatrix<f64>>::new(),
|
||||
backoff_steps: Vec::<i32>::new(),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// --- gram matrix realization ---
|
||||
|
||||
// the Lorentz form
|
||||
lazy_static! {
|
||||
static ref Q: DMatrix<f64> = DMatrix::from_row_slice(5, 5, &[
|
||||
1.0, 0.0, 0.0, 0.0, 0.0,
|
||||
0.0, 1.0, 0.0, 0.0, 0.0,
|
||||
0.0, 0.0, 1.0, 0.0, 0.0,
|
||||
0.0, 0.0, 0.0, 0.0, -2.0,
|
||||
0.0, 0.0, 0.0, -2.0, 0.0
|
||||
]);
|
||||
}
|
||||
|
||||
struct SearchState {
|
||||
config: DMatrix<f64>,
|
||||
err_proj: DMatrix<f64>,
|
||||
loss: f64
|
||||
}
|
||||
|
||||
impl SearchState {
|
||||
fn from_config(gram: &PartialMatrix, config: DMatrix<f64>) -> SearchState {
|
||||
let err_proj = gram.sub_proj(&(config.tr_mul(&*Q) * &config));
|
||||
let loss = err_proj.norm_squared();
|
||||
SearchState {
|
||||
config: config,
|
||||
err_proj: err_proj,
|
||||
loss: loss
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fn basis_matrix(index: (usize, usize), nrows: usize, ncols: usize) -> DMatrix<f64> {
|
||||
let mut result = DMatrix::<f64>::zeros(nrows, ncols);
|
||||
result[index] = 1.0;
|
||||
result
|
||||
}
|
||||
|
||||
// use backtracking line search to find a better configuration
|
||||
fn seek_better_config(
|
||||
gram: &PartialMatrix,
|
||||
state: &SearchState,
|
||||
base_step: &DMatrix<f64>,
|
||||
base_target_improvement: f64,
|
||||
min_efficiency: f64,
|
||||
backoff: f64,
|
||||
max_backoff_steps: i32
|
||||
) -> Option<(SearchState, i32)> {
|
||||
let mut rate = 1.0;
|
||||
for backoff_steps in 0..max_backoff_steps {
|
||||
let trial_config = &state.config + rate * base_step;
|
||||
let trial_state = SearchState::from_config(gram, trial_config);
|
||||
let improvement = state.loss - trial_state.loss;
|
||||
if improvement >= min_efficiency * rate * base_target_improvement {
|
||||
return Some((trial_state, backoff_steps));
|
||||
}
|
||||
rate *= backoff;
|
||||
}
|
||||
None
|
||||
}
|
||||
|
||||
// seek a matrix `config` for which `config' * Q * config` matches the partial
|
||||
// matrix `gram`. use gradient descent starting from `guess`
|
||||
pub fn realize_gram(
|
||||
gram: &PartialMatrix,
|
||||
guess: DMatrix<f64>,
|
||||
frozen: &[(usize, usize)],
|
||||
scaled_tol: f64,
|
||||
min_efficiency: f64,
|
||||
backoff: f64,
|
||||
reg_scale: f64,
|
||||
max_descent_steps: i32,
|
||||
max_backoff_steps: i32
|
||||
) -> (DMatrix<f64>, bool, DescentHistory) {
|
||||
// start the descent history
|
||||
let mut history = DescentHistory::new();
|
||||
|
||||
// find the dimension of the search space
|
||||
let element_dim = guess.nrows();
|
||||
let assembly_dim = guess.ncols();
|
||||
let total_dim = element_dim * assembly_dim;
|
||||
|
||||
// scale the tolerance
|
||||
let scale_adjustment = (gram.0.len() as f64).sqrt();
|
||||
let tol = scale_adjustment * scaled_tol;
|
||||
|
||||
// convert the frozen indices to stacked format
|
||||
let frozen_stacked: Vec<usize> = frozen.into_iter().map(
|
||||
|index| index.1*element_dim + index.0
|
||||
).collect();
|
||||
|
||||
// use Newton's method with backtracking and gradient descent backup
|
||||
let mut state = SearchState::from_config(gram, guess);
|
||||
for _ in 0..max_descent_steps {
|
||||
// stop if the loss is tolerably low
|
||||
history.config.push(state.config.clone());
|
||||
history.scaled_loss.push(state.loss / scale_adjustment);
|
||||
if state.loss < tol { break; }
|
||||
|
||||
// find the negative gradient of the loss function
|
||||
let neg_grad = 4.0 * &*Q * &state.config * &state.err_proj;
|
||||
let mut neg_grad_stacked = neg_grad.clone().reshape_generic(Dyn(total_dim), Const::<1>);
|
||||
history.neg_grad.push(neg_grad.clone());
|
||||
|
||||
// find the negative Hessian of the loss function
|
||||
let mut hess_cols = Vec::<DVector<f64>>::with_capacity(total_dim);
|
||||
for col in 0..assembly_dim {
|
||||
for row in 0..element_dim {
|
||||
let index = (row, col);
|
||||
let basis_mat = basis_matrix(index, element_dim, assembly_dim);
|
||||
let neg_d_err =
|
||||
basis_mat.tr_mul(&*Q) * &state.config
|
||||
+ state.config.tr_mul(&*Q) * &basis_mat;
|
||||
let neg_d_err_proj = gram.proj(&neg_d_err);
|
||||
let deriv_grad = 4.0 * &*Q * (
|
||||
-&basis_mat * &state.err_proj
|
||||
+ &state.config * &neg_d_err_proj
|
||||
);
|
||||
hess_cols.push(deriv_grad.reshape_generic(Dyn(total_dim), Const::<1>));
|
||||
}
|
||||
}
|
||||
let mut hess = DMatrix::from_columns(hess_cols.as_slice());
|
||||
|
||||
// regularize the Hessian
|
||||
let min_eigval = hess.symmetric_eigenvalues().min();
|
||||
if min_eigval <= 0.0 {
|
||||
hess -= reg_scale * min_eigval * DMatrix::identity(total_dim, total_dim);
|
||||
}
|
||||
history.min_eigval.push(min_eigval);
|
||||
|
||||
// project the negative gradient and negative Hessian onto the
|
||||
// orthogonal complement of the frozen subspace
|
||||
let zero_col = DVector::zeros(total_dim);
|
||||
let zero_row = zero_col.transpose();
|
||||
for &k in &frozen_stacked {
|
||||
neg_grad_stacked[k] = 0.0;
|
||||
hess.set_row(k, &zero_row);
|
||||
hess.set_column(k, &zero_col);
|
||||
hess[(k, k)] = 1.0;
|
||||
}
|
||||
|
||||
// compute the Newton step
|
||||
/*
|
||||
we need to either handle or eliminate the case where the minimum
|
||||
eigenvalue of the Hessian is zero, so the regularized Hessian is
|
||||
singular. right now, this causes the Cholesky decomposition to return
|
||||
`None`, leading to a panic when we unrap
|
||||
*/
|
||||
let base_step_stacked = hess.cholesky().unwrap().solve(&neg_grad_stacked);
|
||||
let base_step = base_step_stacked.reshape_generic(Dyn(element_dim), Dyn(assembly_dim));
|
||||
history.base_step.push(base_step.clone());
|
||||
|
||||
// use backtracking line search to find a better configuration
|
||||
match seek_better_config(
|
||||
gram, &state, &base_step, neg_grad.dot(&base_step),
|
||||
min_efficiency, backoff, max_backoff_steps
|
||||
) {
|
||||
Some((better_state, backoff_steps)) => {
|
||||
state = better_state;
|
||||
history.backoff_steps.push(backoff_steps);
|
||||
},
|
||||
None => return (state.config, false, history)
|
||||
};
|
||||
}
|
||||
(state.config, state.loss < tol, history)
|
||||
}
|
||||
|
||||
// --- tests ---
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use std::{array, f64::consts::PI};
|
||||
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn sub_proj_test() {
|
||||
let target = PartialMatrix(vec![
|
||||
MatrixEntry { index: (0, 0), value: 19.0 },
|
||||
MatrixEntry { index: (0, 2), value: 39.0 },
|
||||
MatrixEntry { index: (1, 1), value: 59.0 },
|
||||
MatrixEntry { index: (1, 2), value: 69.0 }
|
||||
]);
|
||||
let attempt = DMatrix::<f64>::from_row_slice(2, 3, &[
|
||||
1.0, 2.0, 3.0,
|
||||
4.0, 5.0, 6.0
|
||||
]);
|
||||
let expected_result = DMatrix::<f64>::from_row_slice(2, 3, &[
|
||||
18.0, 0.0, 36.0,
|
||||
0.0, 54.0, 63.0
|
||||
]);
|
||||
assert_eq!(target.sub_proj(&attempt), expected_result);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn zero_loss_test() {
|
||||
let gram = PartialMatrix({
|
||||
let mut entries = Vec::<MatrixEntry>::new();
|
||||
for j in 0..3 {
|
||||
for k in 0..3 {
|
||||
entries.push(MatrixEntry {
|
||||
index: (j, k),
|
||||
value: if j == k { 1.0 } else { -1.0 }
|
||||
});
|
||||
}
|
||||
}
|
||||
entries
|
||||
});
|
||||
let config = {
|
||||
let a: f64 = 0.75_f64.sqrt();
|
||||
DMatrix::from_columns(&[
|
||||
sphere(1.0, 0.0, 0.0, a),
|
||||
sphere(-0.5, a, 0.0, a),
|
||||
sphere(-0.5, -a, 0.0, a)
|
||||
])
|
||||
};
|
||||
let state = SearchState::from_config(&gram, config);
|
||||
assert!(state.loss.abs() < f64::EPSILON);
|
||||
}
|
||||
|
||||
// this problem is from a sangaku by Irisawa Shintarō Hiroatsu. the article
|
||||
// below includes a nice translation of the problem statement, which was
|
||||
// recorded in Uchida Itsumi's book _Kokon sankan_ (_Mathematics, Past and
|
||||
// Present_)
|
||||
//
|
||||
// "Japan's 'Wasan' Mathematical Tradition", by Abe Haruki
|
||||
// https://www.nippon.com/en/japan-topics/c12801/
|
||||
//
|
||||
#[test]
|
||||
fn irisawa_hexlet_test() {
|
||||
let gram = PartialMatrix({
|
||||
let mut entries = Vec::<MatrixEntry>::new();
|
||||
for s in 0..9 {
|
||||
// each sphere is represented by a spacelike vector
|
||||
entries.push(MatrixEntry { index: (s, s), value: 1.0 });
|
||||
|
||||
// the circumscribing sphere is tangent to all of the other
|
||||
// spheres, with matching orientation
|
||||
if s > 0 {
|
||||
entries.push(MatrixEntry { index: (0, s), value: 1.0 });
|
||||
entries.push(MatrixEntry { index: (s, 0), value: 1.0 });
|
||||
}
|
||||
|
||||
if s > 2 {
|
||||
// each chain sphere is tangent to the "sun" and "moon"
|
||||
// spheres, with opposing orientation
|
||||
for n in 1..3 {
|
||||
entries.push(MatrixEntry { index: (s, n), value: -1.0 });
|
||||
entries.push(MatrixEntry { index: (n, s), value: -1.0 });
|
||||
}
|
||||
|
||||
// each chain sphere is tangent to the next chain sphere,
|
||||
// with opposing orientation
|
||||
let s_next = 3 + (s-2) % 6;
|
||||
entries.push(MatrixEntry { index: (s, s_next), value: -1.0 });
|
||||
entries.push(MatrixEntry { index: (s_next, s), value: -1.0 });
|
||||
}
|
||||
}
|
||||
entries
|
||||
});
|
||||
let guess = DMatrix::from_columns(
|
||||
[
|
||||
sphere(0.0, 0.0, 0.0, 15.0),
|
||||
sphere(0.0, 0.0, -9.0, 5.0),
|
||||
sphere(0.0, 0.0, 11.0, 3.0)
|
||||
].into_iter().chain(
|
||||
(1..=6).map(
|
||||
|k| {
|
||||
let ang = (k as f64) * PI/3.0;
|
||||
sphere(9.0 * ang.cos(), 9.0 * ang.sin(), 0.0, 2.5)
|
||||
}
|
||||
)
|
||||
).collect::<Vec<_>>().as_slice()
|
||||
);
|
||||
let frozen: [(usize, usize); 4] = array::from_fn(|k| (3, k));
|
||||
const SCALED_TOL: f64 = 1.0e-12;
|
||||
let (config, success, history) = realize_gram(
|
||||
&gram, guess, &frozen,
|
||||
SCALED_TOL, 0.5, 0.9, 1.1, 200, 110
|
||||
);
|
||||
let entry_tol = SCALED_TOL.sqrt();
|
||||
let solution_diams = [30.0, 10.0, 6.0, 5.0, 15.0, 10.0, 3.75, 2.5, 2.0 + 8.0/11.0];
|
||||
for (k, diam) in solution_diams.into_iter().enumerate() {
|
||||
assert!((config[(3, k)] - 1.0 / diam).abs() < entry_tol);
|
||||
}
|
||||
print!("\nCompleted Gram matrix:{}", config.tr_mul(&*Q) * &config);
|
||||
if success {
|
||||
println!("Target accuracy achieved!");
|
||||
} else {
|
||||
println!("Failed to reach target accuracy");
|
||||
}
|
||||
println!("Steps: {}", history.scaled_loss.len() - 1);
|
||||
println!("Loss: {}", history.scaled_loss.last().unwrap());
|
||||
if success {
|
||||
println!("\nChain diameters:");
|
||||
println!(" {} sun (given)", 1.0 / config[(3, 3)]);
|
||||
for k in 4..9 {
|
||||
println!(" {} sun", 1.0 / config[(3, k)]);
|
||||
}
|
||||
}
|
||||
println!("\nStep │ Loss\n─────┼────────────────────────────────");
|
||||
for (step, scaled_loss) in history.scaled_loss.into_iter().enumerate() {
|
||||
println!("{:<4} │ {}", step, scaled_loss);
|
||||
}
|
||||
}
|
||||
|
||||
// --- process inspection examples ---
|
||||
|
||||
// these tests are meant for human inspection, not automated use. run them
|
||||
// one at a time in `--nocapture` mode and read through the results and
|
||||
// optimization histories that they print out. the `run-examples` script
|
||||
// will run all of them
|
||||
|
||||
#[test]
|
||||
fn three_spheres_example() {
|
||||
let gram = PartialMatrix({
|
||||
let mut entries = Vec::<MatrixEntry>::new();
|
||||
for j in 0..3 {
|
||||
for k in 0..3 {
|
||||
entries.push(MatrixEntry {
|
||||
index: (j, k),
|
||||
value: if j == k { 1.0 } else { -1.0 }
|
||||
});
|
||||
}
|
||||
}
|
||||
entries
|
||||
});
|
||||
let guess = {
|
||||
let a: f64 = 0.75_f64.sqrt();
|
||||
DMatrix::from_columns(&[
|
||||
sphere(1.0, 0.0, 0.0, 1.0),
|
||||
sphere(-0.5, a, 0.0, 1.0),
|
||||
sphere(-0.5, -a, 0.0, 1.0)
|
||||
])
|
||||
};
|
||||
println!();
|
||||
let (config, success, history) = realize_gram(
|
||||
&gram, guess, &[],
|
||||
1.0e-12, 0.5, 0.9, 1.1, 200, 110
|
||||
);
|
||||
print!("\nCompleted Gram matrix:{}", config.tr_mul(&*Q) * &config);
|
||||
if success {
|
||||
println!("Target accuracy achieved!");
|
||||
} else {
|
||||
println!("Failed to reach target accuracy");
|
||||
}
|
||||
println!("Steps: {}", history.scaled_loss.len() - 1);
|
||||
println!("Loss: {}", history.scaled_loss.last().unwrap());
|
||||
println!("\nStep │ Loss\n─────┼────────────────────────────────");
|
||||
for (step, scaled_loss) in history.scaled_loss.into_iter().enumerate() {
|
||||
println!("{:<4} │ {}", step, scaled_loss);
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn point_on_sphere_example() {
|
||||
let gram = PartialMatrix({
|
||||
let mut entries = Vec::<MatrixEntry>::new();
|
||||
for j in 0..2 {
|
||||
for k in 0..2 {
|
||||
entries.push(MatrixEntry {
|
||||
index: (j, k),
|
||||
value: if (j, k) == (1, 1) { 1.0 } else { 0.0 }
|
||||
});
|
||||
}
|
||||
}
|
||||
entries
|
||||
});
|
||||
let guess = DMatrix::from_columns(&[
|
||||
point(0.0, 0.0, 2.0),
|
||||
sphere(0.0, 0.0, 0.0, 1.0)
|
||||
]);
|
||||
let frozen = [(3, 0)];
|
||||
println!();
|
||||
let (config, success, history) = realize_gram(
|
||||
&gram, guess, &frozen,
|
||||
1.0e-12, 0.5, 0.9, 1.1, 200, 110
|
||||
);
|
||||
print!("\nCompleted Gram matrix:{}", config.tr_mul(&*Q) * &config);
|
||||
print!("Configuration:{}", config);
|
||||
if success {
|
||||
println!("Target accuracy achieved!");
|
||||
} else {
|
||||
println!("Failed to reach target accuracy");
|
||||
}
|
||||
println!("Steps: {}", history.scaled_loss.len() - 1);
|
||||
println!("Loss: {}", history.scaled_loss.last().unwrap());
|
||||
println!("\nStep │ Loss\n─────┼────────────────────────────────");
|
||||
for (step, scaled_loss) in history.scaled_loss.into_iter().enumerate() {
|
||||
println!("{:<4} │ {}", step, scaled_loss);
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1,26 +1,191 @@
|
||||
use itertools::Itertools;
|
||||
use sycamore::{prelude::*, web::tags::div};
|
||||
use web_sys::{Element, KeyboardEvent, MouseEvent, wasm_bindgen::JsCast};
|
||||
use sycamore::prelude::*;
|
||||
use web_sys::{
|
||||
Event,
|
||||
HtmlInputElement,
|
||||
KeyboardEvent,
|
||||
MouseEvent,
|
||||
wasm_bindgen::JsCast
|
||||
};
|
||||
|
||||
use crate::AppState;
|
||||
use crate::{AppState, assembly, assembly::Constraint};
|
||||
|
||||
// this component lists the elements of the assembly, showing the constraints
|
||||
// on each element as a collapsible sub-list. its implementation is based on
|
||||
// Kate Morley's HTML + CSS tree views:
|
||||
// an editable view of the Lorentz product representing a constraint
|
||||
#[component(inline_props)]
|
||||
fn LorentzProductInput(constraint: Constraint) -> View {
|
||||
view! {
|
||||
input(
|
||||
r#type="text",
|
||||
bind:value=constraint.rep_text,
|
||||
on:change=move |event: Event| {
|
||||
let target: HtmlInputElement = event.target().unwrap().unchecked_into();
|
||||
match target.value().parse::<f64>() {
|
||||
Ok(rep) => batch(|| {
|
||||
constraint.rep.set(rep);
|
||||
constraint.rep_valid.set(true);
|
||||
}),
|
||||
Err(_) => constraint.rep_valid.set(false)
|
||||
};
|
||||
}
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
// a list item that shows a constraint in an outline view of an element
|
||||
#[component(inline_props)]
|
||||
fn ConstraintOutlineItem(constraint_key: usize, element_key: usize) -> View {
|
||||
let state = use_context::<AppState>();
|
||||
let assembly = &state.assembly;
|
||||
let constraint = assembly.constraints.with(|csts| csts[constraint_key].clone());
|
||||
let other_arg = if constraint.args.0 == element_key {
|
||||
constraint.args.1
|
||||
} else {
|
||||
constraint.args.0
|
||||
};
|
||||
let other_arg_label = assembly.elements.with(|elts| elts[other_arg].label.clone());
|
||||
let class = constraint.rep_valid.map(
|
||||
|&rep_valid| if rep_valid { "cst" } else { "cst invalid" }
|
||||
);
|
||||
view! {
|
||||
li(class=class.get()) {
|
||||
input(r#type="checkbox", bind:checked=constraint.active)
|
||||
div(class="cst-label") { (other_arg_label) }
|
||||
LorentzProductInput(constraint=constraint)
|
||||
div(class="status")
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// a list item that shows an element in an outline view of an assembly
|
||||
#[component(inline_props)]
|
||||
fn ElementOutlineItem(key: usize, element: assembly::Element) -> View {
|
||||
let state = use_context::<AppState>();
|
||||
let class = state.selection.map(
|
||||
move |sel| if sel.contains(&key) { "selected" } else { "" }
|
||||
);
|
||||
let label = element.label.clone();
|
||||
let rep_components = element.rep.map(
|
||||
|rep| rep.iter().map(
|
||||
|u| format!("{:.3}", u).replace("-", "\u{2212}")
|
||||
).collect()
|
||||
);
|
||||
let constrained = element.constraints.map(|csts| csts.len() > 0);
|
||||
let constraint_list = element.constraints.map(
|
||||
|csts| csts.clone().into_iter().collect()
|
||||
);
|
||||
let details_node = create_node_ref();
|
||||
view! {
|
||||
li {
|
||||
details(ref=details_node) {
|
||||
summary(
|
||||
class=class.get(),
|
||||
on:keydown={
|
||||
move |event: KeyboardEvent| {
|
||||
match event.key().as_str() {
|
||||
"Enter" => {
|
||||
if event.shift_key() {
|
||||
state.selection.update(|sel| {
|
||||
if !sel.remove(&key) {
|
||||
sel.insert(key);
|
||||
}
|
||||
});
|
||||
} else {
|
||||
state.selection.update(|sel| {
|
||||
sel.clear();
|
||||
sel.insert(key);
|
||||
});
|
||||
}
|
||||
event.prevent_default();
|
||||
},
|
||||
"ArrowRight" if constrained.get() => {
|
||||
let _ = details_node
|
||||
.get()
|
||||
.unchecked_into::<web_sys::Element>()
|
||||
.set_attribute("open", "");
|
||||
},
|
||||
"ArrowLeft" => {
|
||||
let _ = details_node
|
||||
.get()
|
||||
.unchecked_into::<web_sys::Element>()
|
||||
.remove_attribute("open");
|
||||
},
|
||||
_ => ()
|
||||
}
|
||||
}
|
||||
}
|
||||
) {
|
||||
div(
|
||||
class="elt-switch",
|
||||
on:click=|event: MouseEvent| event.stop_propagation()
|
||||
)
|
||||
div(
|
||||
class="elt",
|
||||
on:click={
|
||||
move |event: MouseEvent| {
|
||||
if event.shift_key() {
|
||||
state.selection.update(|sel| {
|
||||
if !sel.remove(&key) {
|
||||
sel.insert(key);
|
||||
}
|
||||
});
|
||||
} else {
|
||||
state.selection.update(|sel| {
|
||||
sel.clear();
|
||||
sel.insert(key);
|
||||
});
|
||||
}
|
||||
event.stop_propagation();
|
||||
event.prevent_default();
|
||||
}
|
||||
}
|
||||
) {
|
||||
div(class="elt-label") { (label) }
|
||||
div(class="elt-rep") {
|
||||
Indexed(
|
||||
list=rep_components,
|
||||
view=|coord_str| view! {
|
||||
div { (coord_str) }
|
||||
}
|
||||
)
|
||||
}
|
||||
div(class="status")
|
||||
}
|
||||
}
|
||||
ul(class="constraints") {
|
||||
Keyed(
|
||||
list=constraint_list,
|
||||
view=move |cst_key| view! {
|
||||
ConstraintOutlineItem(
|
||||
constraint_key=cst_key,
|
||||
element_key=key
|
||||
)
|
||||
},
|
||||
key=|cst_key| cst_key.clone()
|
||||
)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// a component that lists the elements of the current assembly, showing the
|
||||
// constraints on each element as a collapsible sub-list. its implementation
|
||||
// is based on Kate Morley's HTML + CSS tree views:
|
||||
//
|
||||
// https://iamkate.com/code/tree-views/
|
||||
//
|
||||
#[component]
|
||||
pub fn Outline() -> View {
|
||||
// sort the elements alphabetically by ID
|
||||
let elements_sorted = create_memo(|| {
|
||||
let state = use_context::<AppState>();
|
||||
state.assembly.elements
|
||||
.get_clone()
|
||||
let state = use_context::<AppState>();
|
||||
|
||||
// list the elements alphabetically by ID
|
||||
let element_list = state.assembly.elements.map(
|
||||
|elts| elts
|
||||
.clone()
|
||||
.into_iter()
|
||||
.sorted_by_key(|(_, elt)| elt.id.clone())
|
||||
.collect()
|
||||
});
|
||||
);
|
||||
|
||||
view! {
|
||||
ul(
|
||||
@ -31,130 +196,11 @@ pub fn Outline() -> View {
|
||||
}
|
||||
) {
|
||||
Keyed(
|
||||
list=elements_sorted,
|
||||
view=|(key, elt)| {
|
||||
let state = use_context::<AppState>();
|
||||
let class = create_memo({
|
||||
move || {
|
||||
if state.selection.with(|sel| sel.contains(&key)) {
|
||||
"selected"
|
||||
} else {
|
||||
""
|
||||
}
|
||||
}
|
||||
});
|
||||
let label = elt.label.clone();
|
||||
let rep_components = elt.rep.iter().map(|u| {
|
||||
let u_coord = u.to_string().replace("-", "\u{2212}");
|
||||
View::from(div().children(u_coord))
|
||||
}).collect::<Vec<_>>();
|
||||
let constrained = elt.constraints.len() > 0;
|
||||
let details_node = create_node_ref();
|
||||
view! {
|
||||
/* [TO DO] switch to integer-valued parameters whenever
|
||||
that becomes possible again */
|
||||
li {
|
||||
details(ref=details_node) {
|
||||
summary(
|
||||
class=class.get(),
|
||||
on:keydown={
|
||||
move |event: KeyboardEvent| {
|
||||
match event.key().as_str() {
|
||||
"Enter" => {
|
||||
if event.shift_key() {
|
||||
state.selection.update(|sel| {
|
||||
if !sel.remove(&key) {
|
||||
sel.insert(key);
|
||||
}
|
||||
});
|
||||
} else {
|
||||
state.selection.update(|sel| {
|
||||
sel.clear();
|
||||
sel.insert(key);
|
||||
});
|
||||
}
|
||||
event.prevent_default();
|
||||
},
|
||||
"ArrowRight" if constrained => {
|
||||
let _ = details_node
|
||||
.get()
|
||||
.unchecked_into::<Element>()
|
||||
.set_attribute("open", "");
|
||||
},
|
||||
"ArrowLeft" => {
|
||||
let _ = details_node
|
||||
.get()
|
||||
.unchecked_into::<Element>()
|
||||
.remove_attribute("open");
|
||||
},
|
||||
_ => ()
|
||||
}
|
||||
}
|
||||
}
|
||||
) {
|
||||
div(
|
||||
class="elt-switch",
|
||||
on:click=|event: MouseEvent| event.stop_propagation()
|
||||
)
|
||||
div(
|
||||
class="elt",
|
||||
on:click={
|
||||
move |event: MouseEvent| {
|
||||
if event.shift_key() {
|
||||
state.selection.update(|sel| {
|
||||
if !sel.remove(&key) {
|
||||
sel.insert(key);
|
||||
}
|
||||
});
|
||||
} else {
|
||||
state.selection.update(|sel| {
|
||||
sel.clear();
|
||||
sel.insert(key);
|
||||
});
|
||||
}
|
||||
event.stop_propagation();
|
||||
event.prevent_default();
|
||||
}
|
||||
}
|
||||
) {
|
||||
div(class="elt-label") { (label) }
|
||||
div(class="elt-rep") { (rep_components) }
|
||||
}
|
||||
}
|
||||
ul(class="constraints") {
|
||||
Keyed(
|
||||
list=elt.constraints.into_iter().collect::<Vec<_>>(),
|
||||
view=move |c_key: usize| {
|
||||
let c_state = use_context::<AppState>();
|
||||
let assembly = &c_state.assembly;
|
||||
let cst = assembly.constraints.with(|csts| csts[c_key].clone());
|
||||
let other_arg = if cst.args.0 == key {
|
||||
cst.args.1
|
||||
} else {
|
||||
cst.args.0
|
||||
};
|
||||
let other_arg_label = assembly.elements.with(|elts| elts[other_arg].label.clone());
|
||||
view! {
|
||||
li(class="cst") {
|
||||
input(r#type="checkbox", bind:checked=cst.active)
|
||||
div(class="cst-label") { (other_arg_label) }
|
||||
div(class="cst-rep") { (cst.rep) }
|
||||
}
|
||||
}
|
||||
},
|
||||
key=|c_key| c_key.clone()
|
||||
)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
list=element_list,
|
||||
view=|(key, elt)| view! {
|
||||
ElementOutlineItem(key=key, element=elt)
|
||||
},
|
||||
key=|(key, elt)| (
|
||||
key.clone(),
|
||||
elt.id.clone(),
|
||||
elt.label.clone(),
|
||||
elt.constraints.clone()
|
||||
)
|
||||
key=|(key, _)| key.clone()
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
@ -8,7 +8,8 @@ using Optim
|
||||
|
||||
export
|
||||
rand_on_shell, Q, DescentHistory,
|
||||
realize_gram_gradient, realize_gram_newton, realize_gram_optim, realize_gram
|
||||
realize_gram_gradient, realize_gram_newton, realize_gram_optim,
|
||||
realize_gram_alt_proj, realize_gram
|
||||
|
||||
# === guessing ===
|
||||
|
||||
@ -143,7 +144,7 @@ function realize_gram_gradient(
|
||||
break
|
||||
end
|
||||
|
||||
# find negative gradient of loss function
|
||||
# find the negative gradient of the loss function
|
||||
neg_grad = 4*Q*L*Δ_proj
|
||||
slope = norm(neg_grad)
|
||||
dir = neg_grad / slope
|
||||
@ -232,7 +233,7 @@ function realize_gram_newton(
|
||||
break
|
||||
end
|
||||
|
||||
# find the negative gradient of loss function
|
||||
# find the negative gradient of the loss function
|
||||
neg_grad = 4*Q*L*Δ_proj
|
||||
|
||||
# find the negative Hessian of the loss function
|
||||
@ -313,6 +314,129 @@ function realize_gram_optim(
|
||||
)
|
||||
end
|
||||
|
||||
# seek a matrix `L` for which `L'QL` matches the sparse matrix `gram` at every
|
||||
# explicit entry of `gram`. use gradient descent starting from `guess`, with an
|
||||
# alternate technique for finding the projected base step from the unprojected
|
||||
# Hessian
|
||||
function realize_gram_alt_proj(
|
||||
gram::SparseMatrixCSC{T, <:Any},
|
||||
guess::Matrix{T},
|
||||
frozen = CartesianIndex[];
|
||||
scaled_tol = 1e-30,
|
||||
min_efficiency = 0.5,
|
||||
backoff = 0.9,
|
||||
reg_scale = 1.1,
|
||||
max_descent_steps = 200,
|
||||
max_backoff_steps = 110
|
||||
) where T <: Number
|
||||
# start history
|
||||
history = DescentHistory{T}()
|
||||
|
||||
# find the dimension of the search space
|
||||
dims = size(guess)
|
||||
element_dim, construction_dim = dims
|
||||
total_dim = element_dim * construction_dim
|
||||
|
||||
# list the constrained entries of the gram matrix
|
||||
J, K, _ = findnz(gram)
|
||||
constrained = zip(J, K)
|
||||
|
||||
# scale the tolerance
|
||||
scale_adjustment = sqrt(T(length(constrained)))
|
||||
tol = scale_adjustment * scaled_tol
|
||||
|
||||
# convert the frozen indices to stacked format
|
||||
frozen_stacked = [(index[2]-1)*element_dim + index[1] for index in frozen]
|
||||
|
||||
# initialize search state
|
||||
L = copy(guess)
|
||||
Δ_proj = proj_diff(gram, L'*Q*L)
|
||||
loss = dot(Δ_proj, Δ_proj)
|
||||
|
||||
# use Newton's method with backtracking and gradient descent backup
|
||||
for step in 1:max_descent_steps
|
||||
# stop if the loss is tolerably low
|
||||
if loss < tol
|
||||
break
|
||||
end
|
||||
|
||||
# find the negative gradient of the loss function
|
||||
neg_grad = 4*Q*L*Δ_proj
|
||||
|
||||
# find the negative Hessian of the loss function
|
||||
hess = Matrix{T}(undef, total_dim, total_dim)
|
||||
indices = [(j, k) for k in 1:construction_dim for j in 1:element_dim]
|
||||
for (j, k) in indices
|
||||
basis_mat = basis_matrix(T, j, k, dims)
|
||||
neg_dΔ = basis_mat'*Q*L + L'*Q*basis_mat
|
||||
neg_dΔ_proj = proj_to_entries(neg_dΔ, constrained)
|
||||
deriv_grad = 4*Q*(-basis_mat*Δ_proj + L*neg_dΔ_proj)
|
||||
hess[:, (k-1)*element_dim + j] = reshape(deriv_grad, total_dim)
|
||||
end
|
||||
hess_sym = Hermitian(hess)
|
||||
push!(history.hess, hess_sym)
|
||||
|
||||
# regularize the Hessian
|
||||
min_eigval = minimum(eigvals(hess_sym))
|
||||
push!(history.positive, min_eigval > 0)
|
||||
if min_eigval <= 0
|
||||
hess -= reg_scale * min_eigval * I
|
||||
end
|
||||
|
||||
# compute the Newton step
|
||||
neg_grad_stacked = reshape(neg_grad, total_dim)
|
||||
for k in frozen_stacked
|
||||
neg_grad_stacked[k] = 0
|
||||
hess[k, :] .= 0
|
||||
hess[:, k] .= 0
|
||||
hess[k, k] = 1
|
||||
end
|
||||
base_step_stacked = Hermitian(hess) \ neg_grad_stacked
|
||||
base_step = reshape(base_step_stacked, dims)
|
||||
push!(history.base_step, base_step)
|
||||
|
||||
# store the current position, loss, and slope
|
||||
L_last = L
|
||||
loss_last = loss
|
||||
push!(history.scaled_loss, loss / scale_adjustment)
|
||||
push!(history.neg_grad, neg_grad)
|
||||
push!(history.slope, norm(neg_grad))
|
||||
|
||||
# find a good step size using backtracking line search
|
||||
push!(history.stepsize, 0)
|
||||
push!(history.backoff_steps, max_backoff_steps)
|
||||
empty!(history.last_line_L)
|
||||
empty!(history.last_line_loss)
|
||||
rate = one(T)
|
||||
step_success = false
|
||||
base_target_improvement = dot(neg_grad, base_step)
|
||||
for backoff_steps in 0:max_backoff_steps
|
||||
history.stepsize[end] = rate
|
||||
L = L_last + rate * base_step
|
||||
Δ_proj = proj_diff(gram, L'*Q*L)
|
||||
loss = dot(Δ_proj, Δ_proj)
|
||||
improvement = loss_last - loss
|
||||
push!(history.last_line_L, L)
|
||||
push!(history.last_line_loss, loss / scale_adjustment)
|
||||
if improvement >= min_efficiency * rate * base_target_improvement
|
||||
history.backoff_steps[end] = backoff_steps
|
||||
step_success = true
|
||||
break
|
||||
end
|
||||
rate *= backoff
|
||||
end
|
||||
|
||||
# if we've hit a wall, quit
|
||||
if !step_success
|
||||
return L_last, false, history
|
||||
end
|
||||
end
|
||||
|
||||
# return the factorization and its history
|
||||
push!(history.scaled_loss, loss / scale_adjustment)
|
||||
L, loss < tol, history
|
||||
end
|
||||
|
||||
# seek a matrix `L` for which `L'QL` matches the sparse matrix `gram` at every
|
||||
# explicit entry of `gram`. use gradient descent starting from `guess`
|
||||
function realize_gram(
|
||||
@ -321,7 +445,6 @@ function realize_gram(
|
||||
frozen = nothing;
|
||||
scaled_tol = 1e-30,
|
||||
min_efficiency = 0.5,
|
||||
init_rate = 1.0,
|
||||
backoff = 0.9,
|
||||
reg_scale = 1.1,
|
||||
max_descent_steps = 200,
|
||||
@ -352,20 +475,19 @@ function realize_gram(
|
||||
unfrozen_stacked = reshape(is_unfrozen, total_dim)
|
||||
end
|
||||
|
||||
# initialize variables
|
||||
grad_rate = init_rate
|
||||
# initialize search state
|
||||
L = copy(guess)
|
||||
|
||||
# use Newton's method with backtracking and gradient descent backup
|
||||
Δ_proj = proj_diff(gram, L'*Q*L)
|
||||
loss = dot(Δ_proj, Δ_proj)
|
||||
|
||||
# use Newton's method with backtracking and gradient descent backup
|
||||
for step in 1:max_descent_steps
|
||||
# stop if the loss is tolerably low
|
||||
if loss < tol
|
||||
break
|
||||
end
|
||||
|
||||
# find the negative gradient of loss function
|
||||
# find the negative gradient of the loss function
|
||||
neg_grad = 4*Q*L*Δ_proj
|
||||
|
||||
# find the negative Hessian of the loss function
|
||||
@ -420,6 +542,7 @@ function realize_gram(
|
||||
empty!(history.last_line_loss)
|
||||
rate = one(T)
|
||||
step_success = false
|
||||
base_target_improvement = dot(neg_grad, base_step)
|
||||
for backoff_steps in 0:max_backoff_steps
|
||||
history.stepsize[end] = rate
|
||||
L = L_last + rate * base_step
|
||||
@ -428,7 +551,7 @@ function realize_gram(
|
||||
improvement = loss_last - loss
|
||||
push!(history.last_line_L, L)
|
||||
push!(history.last_line_loss, loss / scale_adjustment)
|
||||
if improvement >= min_efficiency * rate * dot(neg_grad, base_step)
|
||||
if improvement >= min_efficiency * rate * base_target_improvement
|
||||
history.backoff_steps[end] = backoff_steps
|
||||
step_success = true
|
||||
break
|
||||
|
||||
@ -75,3 +75,12 @@ if success
|
||||
println(" ", 1 / L[4,k], " sun")
|
||||
end
|
||||
end
|
||||
|
||||
# test an alternate technique for finding the projected base step from the
|
||||
# unprojected Hessian
|
||||
L_alt, success_alt, history_alt = Engine.realize_gram_alt_proj(gram, guess, frozen)
|
||||
completed_gram_alt = L_alt'*Engine.Q*L_alt
|
||||
println("\nDifference in result using alternate projection:\n")
|
||||
display(completed_gram_alt - completed_gram)
|
||||
println("\nDifference in steps: ", size(history_alt.scaled_loss, 1) - size(history.scaled_loss, 1))
|
||||
println("Difference in loss: ", history_alt.scaled_loss[end] - history.scaled_loss[end], "\n")
|
||||
@ -65,3 +65,12 @@ else
|
||||
end
|
||||
println("Steps: ", size(history.scaled_loss, 1))
|
||||
println("Loss: ", history.scaled_loss[end], "\n")
|
||||
|
||||
# test an alternate technique for finding the projected base step from the
|
||||
# unprojected Hessian
|
||||
L_alt, success_alt, history_alt = Engine.realize_gram_alt_proj(gram, guess, frozen)
|
||||
completed_gram_alt = L_alt'*Engine.Q*L_alt
|
||||
println("\nDifference in result using alternate projection:\n")
|
||||
display(completed_gram_alt - completed_gram)
|
||||
println("\nDifference in steps: ", size(history_alt.scaled_loss, 1) - size(history.scaled_loss, 1))
|
||||
println("Difference in loss: ", history_alt.scaled_loss[end] - history.scaled_loss[end], "\n")
|
||||
@ -94,3 +94,12 @@ if success
|
||||
radius_ratio = dot(infty, Engine.Q * L[:,5]) / dot(infty, Engine.Q * L[:,6])
|
||||
println("\nCircumradius / inradius: ", radius_ratio)
|
||||
end
|
||||
|
||||
# test an alternate technique for finding the projected base step from the
|
||||
# unprojected Hessian
|
||||
L_alt, success_alt, history_alt = Engine.realize_gram_alt_proj(gram, guess, frozen)
|
||||
completed_gram_alt = L_alt'*Engine.Q*L_alt
|
||||
println("\nDifference in result using alternate projection:\n")
|
||||
display(completed_gram_alt - completed_gram)
|
||||
println("\nDifference in steps: ", size(history_alt.scaled_loss, 1) - size(history.scaled_loss, 1))
|
||||
println("Difference in loss: ", history_alt.scaled_loss[end] - history.scaled_loss[end], "\n")
|
||||
Loading…
Reference in New Issue
Block a user