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24 Commits

Author SHA1 Message Date
Aaron Fenyes
5332fda6e4 Move new test to avoid merge conflict 2024-11-11 15:41:42 -08:00
Aaron Fenyes
22a93bee28 Confirm that frozen entries are frozen exactly 2024-11-11 15:34:51 -08:00
Aaron Fenyes
5839882ed7 Name constraint Lorentz product more descriptively 2024-11-11 00:27:28 -08:00
Aaron Fenyes
a4ec52a4e7 Alias the type of an element's color 2024-11-11 00:04:48 -08:00
abb9d35335 Correct align environment in notes 2024-11-11 07:56:27 +00:00
Aaron Fenyes
a170492e3d Add engine conventions to inversive coordinates notes 2024-11-10 23:47:34 -08:00
Aaron Fenyes
b8ca1139d5 Explain what the Element::index field holds
Also, remind us to make the field private when that becomes possible.
2024-11-10 23:22:30 -08:00
Aaron Fenyes
ced001bbfe Alias the types of element and constraint keys
This will make it easier to change the key types if we change how we
store and access elements and constraints.
2024-11-10 22:55:58 -08:00
Aaron Fenyes
ed1890bffc Improve naming of constraint subjects 2024-11-10 19:36:40 -08:00
Aaron Fenyes
da008fd090 Write out representation in Element structure 2024-11-10 19:24:26 -08:00
Aaron Fenyes
933f05661d Only compile engine::point when it's used
This function will eventually be used in the application, but right now
it's only used in tests.
2024-11-10 16:31:29 -08:00
Aaron Fenyes
9c191ae586 Polish log messages 2024-10-30 00:27:16 -07:00
Aaron Fenyes
9e31037e17 Spread web-sys imports over multiple lines 2024-10-30 00:19:44 -07:00
Aaron Fenyes
c2e3c64d4a Remove debug log from Lorentz product input 2024-10-30 00:16:34 -07:00
Aaron Fenyes
76ad4245d5 Factor out Lorentz product input 2024-10-29 23:43:41 -07:00
Aaron Fenyes
a46ef2c8d6 Work around data binding bug in number input
Setting `bind:value` or `bind:valueAsNumber` for a number input seems to
restrict what you can type in it. We work around this by switching to
text inputs for now. We should probably switch back to number inputs if
we can, though, because they let us take advantage of the browser's
parsing and validation.
2024-10-29 22:53:48 -07:00
Aaron Fenyes
e0880d2ad2 Make constraints editable 2024-10-29 22:32:00 -07:00
Aaron Fenyes
e5f4d523f9 Update the realization when a constraint is activated
Sycamore probably has a better way to do this, but this way works for
now.
2024-10-29 13:46:15 -07:00
Aaron Fenyes
a37c71153d Enforce constraints in the editor 2024-10-26 23:51:27 -07:00
Aaron Fenyes
ce33bbf418 Record optimization history 2024-10-26 01:07:17 -07:00
Aaron Fenyes
9f8632efb3 Port the Irisawa hexlet test to Rust
In the process, notice that the tolerance scale adjustment was ported
wrong, and correct it.
2024-10-25 21:43:53 -07:00
Aaron Fenyes
9fe03264ab Port the Gram matrix realization routine to Rust
Validate with the process inspection example tests, which print out
their results and optimization histories when run one at a time in
`--nocapture` mode.
2024-10-25 17:34:29 -07:00
Aaron Fenyes
e59d60bf77 Reorganize search state; remove unused variables 2024-10-25 17:17:49 -07:00
Aaron Fenyes
16df161fe7 Test alternate projection technique 2024-10-24 19:51:10 -07:00
14 changed files with 947 additions and 93 deletions

View File

@ -10,6 +10,7 @@ default = ["console_error_panic_hook"]
[dependencies] [dependencies]
itertools = "0.13.0" itertools = "0.13.0"
js-sys = "0.3.70" js-sys = "0.3.70"
lazy_static = "1.5.0"
nalgebra = "0.33.0" nalgebra = "0.33.0"
rustc-hash = "2.0.0" rustc-hash = "2.0.0"
slab = "0.4.9" slab = "0.4.9"
@ -25,6 +26,7 @@ console_error_panic_hook = { version = "0.1.7", optional = true }
version = "0.3.69" version = "0.3.69"
features = [ features = [
'HtmlCanvasElement', 'HtmlCanvasElement',
'HtmlInputElement',
'Performance', 'Performance',
'WebGl2RenderingContext', 'WebGl2RenderingContext',
'WebGlBuffer', 'WebGlBuffer',

View File

@ -93,7 +93,7 @@ details[open]:has(li) .elt-switch::after {
display: flex; display: flex;
} }
.elt-rep > div, .cst-rep { .elt-rep > div {
padding: 2px 0px 0px 0px; padding: 2px 0px 0px 0px;
font-size: 10pt; font-size: 10pt;
text-align: center; text-align: center;
@ -104,10 +104,17 @@ details[open]:has(li) .elt-switch::after {
font-style: italic; font-style: italic;
} }
.cst > input { .cst > input[type=checkbox] {
margin: 0px 8px 0px 0px; margin: 0px 8px 0px 0px;
} }
.cst > input[type=text] {
color: #fcfcfc;
background-color: inherit;
border: 1px solid #555;
border-radius: 2px;
}
/* display */ /* display */
canvas { canvas {

8
app-proto/run-examples Executable file
View File

@ -0,0 +1,8 @@
# based on "Enabling print statements in Cargo tests", by Jon Almeida
#
# https://jonalmeida.com/posts/2015/01/23/print-cargo/
#
cargo test -- --nocapture engine::tests::irisawa_hexlet_test
cargo test -- --nocapture engine::tests::three_spheres_example
cargo test -- --nocapture engine::tests::point_on_sphere_example

View File

@ -11,8 +11,9 @@ fn load_gen_assemb(assembly: &Assembly) {
id: String::from("gemini_a"), id: String::from("gemini_a"),
label: String::from("Castor"), label: String::from("Castor"),
color: [1.00_f32, 0.25_f32, 0.00_f32], color: [1.00_f32, 0.25_f32, 0.00_f32],
rep: engine::sphere(0.5, 0.5, 0.0, 1.0), representation: engine::sphere(0.5, 0.5, 0.0, 1.0),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
index: 0
} }
); );
let _ = assembly.try_insert_element( let _ = assembly.try_insert_element(
@ -20,8 +21,9 @@ fn load_gen_assemb(assembly: &Assembly) {
id: String::from("gemini_b"), id: String::from("gemini_b"),
label: String::from("Pollux"), label: String::from("Pollux"),
color: [0.00_f32, 0.25_f32, 1.00_f32], color: [0.00_f32, 0.25_f32, 1.00_f32],
rep: engine::sphere(-0.5, -0.5, 0.0, 1.0), representation: engine::sphere(-0.5, -0.5, 0.0, 1.0),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
index: 0
} }
); );
let _ = assembly.try_insert_element( let _ = assembly.try_insert_element(
@ -29,8 +31,9 @@ fn load_gen_assemb(assembly: &Assembly) {
id: String::from("ursa_major"), id: String::from("ursa_major"),
label: String::from("Ursa major"), label: String::from("Ursa major"),
color: [0.25_f32, 0.00_f32, 1.00_f32], color: [0.25_f32, 0.00_f32, 1.00_f32],
rep: engine::sphere(-0.5, 0.5, 0.0, 0.75), representation: engine::sphere(-0.5, 0.5, 0.0, 0.75),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
index: 0
} }
); );
let _ = assembly.try_insert_element( let _ = assembly.try_insert_element(
@ -38,8 +41,9 @@ fn load_gen_assemb(assembly: &Assembly) {
id: String::from("ursa_minor"), id: String::from("ursa_minor"),
label: String::from("Ursa minor"), label: String::from("Ursa minor"),
color: [0.25_f32, 1.00_f32, 0.00_f32], color: [0.25_f32, 1.00_f32, 0.00_f32],
rep: engine::sphere(0.5, -0.5, 0.0, 0.5), representation: engine::sphere(0.5, -0.5, 0.0, 0.5),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
index: 0
} }
); );
let _ = assembly.try_insert_element( let _ = assembly.try_insert_element(
@ -47,8 +51,9 @@ fn load_gen_assemb(assembly: &Assembly) {
id: String::from("moon_deimos"), id: String::from("moon_deimos"),
label: String::from("Deimos"), label: String::from("Deimos"),
color: [0.75_f32, 0.75_f32, 0.00_f32], color: [0.75_f32, 0.75_f32, 0.00_f32],
rep: engine::sphere(0.0, 0.15, 1.0, 0.25), representation: engine::sphere(0.0, 0.15, 1.0, 0.25),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
index: 0
} }
); );
let _ = assembly.try_insert_element( let _ = assembly.try_insert_element(
@ -56,18 +61,9 @@ fn load_gen_assemb(assembly: &Assembly) {
id: String::from("moon_phobos"), id: String::from("moon_phobos"),
label: String::from("Phobos"), label: String::from("Phobos"),
color: [0.00_f32, 0.75_f32, 0.50_f32], color: [0.00_f32, 0.75_f32, 0.50_f32],
rep: engine::sphere(0.0, -0.15, -1.0, 0.25), representation: engine::sphere(0.0, -0.15, -1.0, 0.25),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
} index: 0
);
assembly.insert_constraint(
Constraint {
args: (
assembly.elements_by_id.with_untracked(|elts_by_id| elts_by_id["gemini_a"]),
assembly.elements_by_id.with_untracked(|elts_by_id| elts_by_id["gemini_b"])
),
rep: 0.5,
active: create_signal(true)
} }
); );
} }
@ -80,8 +76,9 @@ fn load_low_curv_assemb(assembly: &Assembly) {
id: "central".to_string(), id: "central".to_string(),
label: "Central".to_string(), label: "Central".to_string(),
color: [0.75_f32, 0.75_f32, 0.75_f32], color: [0.75_f32, 0.75_f32, 0.75_f32],
rep: engine::sphere(0.0, 0.0, 0.0, 1.0), representation: engine::sphere(0.0, 0.0, 0.0, 1.0),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
index: 0
} }
); );
let _ = assembly.try_insert_element( let _ = assembly.try_insert_element(
@ -89,8 +86,9 @@ fn load_low_curv_assemb(assembly: &Assembly) {
id: "assemb_plane".to_string(), id: "assemb_plane".to_string(),
label: "Assembly plane".to_string(), label: "Assembly plane".to_string(),
color: [0.75_f32, 0.75_f32, 0.75_f32], color: [0.75_f32, 0.75_f32, 0.75_f32],
rep: engine::sphere_with_offset(0.0, 0.0, 1.0, 0.0, 0.0), representation: engine::sphere_with_offset(0.0, 0.0, 1.0, 0.0, 0.0),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
index: 0
} }
); );
let _ = assembly.try_insert_element( let _ = assembly.try_insert_element(
@ -98,8 +96,9 @@ fn load_low_curv_assemb(assembly: &Assembly) {
id: "side1".to_string(), id: "side1".to_string(),
label: "Side 1".to_string(), label: "Side 1".to_string(),
color: [1.00_f32, 0.00_f32, 0.25_f32], 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), representation: engine::sphere_with_offset(1.0, 0.0, 0.0, 1.0, 0.0),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
index: 0
} }
); );
let _ = assembly.try_insert_element( let _ = assembly.try_insert_element(
@ -107,8 +106,9 @@ fn load_low_curv_assemb(assembly: &Assembly) {
id: "side2".to_string(), id: "side2".to_string(),
label: "Side 2".to_string(), label: "Side 2".to_string(),
color: [0.25_f32, 1.00_f32, 0.00_f32], color: [0.25_f32, 1.00_f32, 0.00_f32],
rep: engine::sphere_with_offset(-0.5, a, 0.0, 1.0, 0.0), representation: engine::sphere_with_offset(-0.5, a, 0.0, 1.0, 0.0),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
index: 0
} }
); );
let _ = assembly.try_insert_element( let _ = assembly.try_insert_element(
@ -116,8 +116,9 @@ fn load_low_curv_assemb(assembly: &Assembly) {
id: "side3".to_string(), id: "side3".to_string(),
label: "Side 3".to_string(), label: "Side 3".to_string(),
color: [0.00_f32, 0.25_f32, 1.00_f32], color: [0.00_f32, 0.25_f32, 1.00_f32],
rep: engine::sphere_with_offset(-0.5, -a, 0.0, 1.0, 0.0), representation: engine::sphere_with_offset(-0.5, -a, 0.0, 1.0, 0.0),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
index: 0
} }
); );
let _ = assembly.try_insert_element( let _ = assembly.try_insert_element(
@ -125,8 +126,9 @@ fn load_low_curv_assemb(assembly: &Assembly) {
id: "corner1".to_string(), id: "corner1".to_string(),
label: "Corner 1".to_string(), label: "Corner 1".to_string(),
color: [0.75_f32, 0.75_f32, 0.75_f32], 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), representation: engine::sphere(-4.0/3.0, 0.0, 0.0, 1.0/3.0),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
index: 0
} }
); );
let _ = assembly.try_insert_element( let _ = assembly.try_insert_element(
@ -134,8 +136,9 @@ fn load_low_curv_assemb(assembly: &Assembly) {
id: "corner2".to_string(), id: "corner2".to_string(),
label: "Corner 2".to_string(), label: "Corner 2".to_string(),
color: [0.75_f32, 0.75_f32, 0.75_f32], 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), representation: engine::sphere(2.0/3.0, -4.0/3.0 * a, 0.0, 1.0/3.0),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
index: 0
} }
); );
let _ = assembly.try_insert_element( let _ = assembly.try_insert_element(
@ -143,8 +146,9 @@ fn load_low_curv_assemb(assembly: &Assembly) {
id: String::from("corner3"), id: String::from("corner3"),
label: String::from("Corner 3"), label: String::from("Corner 3"),
color: [0.75_f32, 0.75_f32, 0.75_f32], 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), representation: engine::sphere(2.0/3.0, 4.0/3.0 * a, 0.0, 1.0/3.0),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
index: 0
} }
); );
} }
@ -204,33 +208,51 @@ pub fn AddRemove() -> View {
}, },
on:click=|_| { on:click=|_| {
let state = use_context::<AppState>(); let state = use_context::<AppState>();
let args = state.selection.with( let subjects = state.selection.with(
|sel| { |sel| {
let arg_vec: Vec<_> = sel.into_iter().collect(); let subject_vec: Vec<_> = sel.into_iter().collect();
(arg_vec[0].clone(), arg_vec[1].clone()) (subject_vec[0].clone(), subject_vec[1].clone())
} }
); );
let lorentz_prod = create_signal(0.0);
let active = create_signal(true);
state.assembly.insert_constraint(Constraint { state.assembly.insert_constraint(Constraint {
args: args, subjects: subjects,
rep: 0.0, lorentz_prod: lorentz_prod,
active: create_signal(true) lorentz_prod_text: create_signal(String::new()),
lorentz_prod_valid: create_signal(false),
active: active,
}); });
state.assembly.realize();
state.selection.update(|sel| sel.clear()); state.selection.update(|sel| sel.clear());
/* DEBUG */ /* DEBUG */
// print updated constraint list // print updated constraint list
console::log_1(&JsValue::from("constraints:")); console::log_1(&JsValue::from("Constraints:"));
state.assembly.constraints.with(|csts| { state.assembly.constraints.with(|csts| {
for (_, cst) in csts.into_iter() { for (_, cst) in csts.into_iter() {
console::log_5( console::log_5(
&JsValue::from(" "), &JsValue::from(" "),
&JsValue::from(cst.args.0), &JsValue::from(cst.subjects.0),
&JsValue::from(cst.args.1), &JsValue::from(cst.subjects.1),
&JsValue::from(":"), &JsValue::from(":"),
&JsValue::from(cst.rep) &JsValue::from(cst.lorentz_prod.get_untracked())
); );
} }
}); });
// update the realization when the constraint activated, or
// edited while active
create_effect(move || {
lorentz_prod.track();
console::log_2(
&JsValue::from("Lorentz product updated to"),
&JsValue::from(lorentz_prod.get_untracked())
);
if active.get() {
state.assembly.realize();
}
});
} }
) { "🔗" } ) { "🔗" }
select(bind:value=assembly_name) { /* DEBUG */ select(bind:value=assembly_name) { /* DEBUG */

View File

@ -1,22 +1,40 @@
use nalgebra::DVector; use nalgebra::{DMatrix, DVector};
use rustc_hash::FxHashMap; use rustc_hash::FxHashMap;
use slab::Slab; use slab::Slab;
use std::collections::BTreeSet; use std::collections::BTreeSet;
use sycamore::prelude::*; use sycamore::prelude::*;
use web_sys::{console, wasm_bindgen::JsValue}; /* DEBUG */
use crate::engine::{realize_gram, PartialMatrix};
// the types of the keys we use to access an assembly's elements and constraints
pub type ElementKey = usize;
pub type ConstraintKey = usize;
pub type ElementColor = [f32; 3];
#[derive(Clone, PartialEq)] #[derive(Clone, PartialEq)]
pub struct Element { pub struct Element {
pub id: String, pub id: String,
pub label: String, pub label: String,
pub color: [f32; 3], pub color: ElementColor,
pub rep: DVector<f64>, pub representation: DVector<f64>,
pub constraints: BTreeSet<usize> pub constraints: BTreeSet<ConstraintKey>,
// the configuration matrix column index that was assigned to this element
// last time the assembly was realized
/* TO DO */
// this is public, as a kludge, because `Element` doesn't have a constructor
// yet. it should be made private as soon as the constructor is written
pub index: usize
} }
#[derive(Clone)] #[derive(Clone)]
pub struct Constraint { pub struct Constraint {
pub args: (usize, usize), pub subjects: (ElementKey, ElementKey),
pub rep: f64, pub lorentz_prod: Signal<f64>,
pub lorentz_prod_text: Signal<String>,
pub lorentz_prod_valid: Signal<bool>,
pub active: Signal<bool> pub active: Signal<bool>
} }
@ -28,7 +46,7 @@ pub struct Assembly {
pub constraints: Signal<Slab<Constraint>>, pub constraints: Signal<Slab<Constraint>>,
// indexing // indexing
pub elements_by_id: Signal<FxHashMap<String, usize>> pub elements_by_id: Signal<FxHashMap<String, ElementKey>>
} }
impl Assembly { impl Assembly {
@ -40,6 +58,8 @@ impl Assembly {
} }
} }
// --- inserting elements and constraints ---
// insert an element into the assembly without checking whether we already // insert an element into the assembly without checking whether we already
// have an element with the same identifier. any element that does have the // 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 // same identifier will get kicked out of the `elements_by_id` index
@ -76,18 +96,100 @@ impl Assembly {
id: id, id: id,
label: format!("Sphere {}", id_num), label: format!("Sphere {}", id_num),
color: [0.75_f32, 0.75_f32, 0.75_f32], 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]), representation: DVector::<f64>::from_column_slice(&[0.0, 0.0, 0.0, 0.5, -0.5]),
constraints: BTreeSet::default() constraints: BTreeSet::default(),
index: 0
} }
); );
} }
pub fn insert_constraint(&self, constraint: Constraint) { pub fn insert_constraint(&self, constraint: Constraint) {
let args = constraint.args; let subjects = constraint.subjects;
let key = self.constraints.update(|csts| csts.insert(constraint)); let key = self.constraints.update(|csts| csts.insert(constraint));
self.elements.update(|elts| { self.elements.update(|elts| {
elts[args.0].constraints.insert(key); elts[subjects.0].constraints.insert(key);
elts[args.1].constraints.insert(key); elts[subjects.1].constraints.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.lorentz_prod_valid.get_untracked() {
let subjects = cst.subjects;
let row = elts[subjects.0].index;
let col = elts[subjects.1].index;
gram_to_be.push_sym(row, col, cst.lorentz_prod.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.representation);
}
(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
self.elements.update(|elts| {
for (_, elt) in elts.iter_mut() {
elt.representation.set_column(0, &config.column(elt.index));
}
});
}
} }
} }

View File

@ -297,7 +297,9 @@ pub fn Display() -> View {
// get the assembly // get the assembly
let elements = state.assembly.elements.get_clone(); let elements = state.assembly.elements.get_clone();
let element_iter = (&elements).into_iter(); let element_iter = (&elements).into_iter();
let reps_world: Vec<_> = element_iter.clone().map(|(_, elt)| &assembly_to_world * &elt.rep).collect(); let reps_world: Vec<_> = element_iter.clone().map(
|(_, elt)| &assembly_to_world * &elt.representation
).collect();
let colors: Vec<_> = element_iter.clone().map(|(key, elt)| let colors: Vec<_> = element_iter.clone().map(|(key, elt)|
if state.selection.with(|sel| sel.contains(&key)) { if state.selection.with(|sel| sel.contains(&key)) {
elt.color.map(|ch| 0.2 + 0.8*ch) elt.color.map(|ch| 0.2 + 0.8*ch)

View File

@ -1,4 +1,13 @@
use nalgebra::DVector; use lazy_static::lazy_static;
use nalgebra::{Const, DMatrix, DVector, Dyn};
use web_sys::{console, wasm_bindgen::JsValue}; /* DEBUG */
// --- elements ---
#[cfg(test)]
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 // 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> { pub fn sphere(center_x: f64, center_y: f64, center_z: f64, radius: f64) -> DVector<f64> {
@ -25,3 +34,507 @@ 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) 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);
}
}
/* TO DO */
// --- new test placed here to avoid merge conflict ---
// at the frozen indices, the optimization steps should have exact zeros,
// and the realized configuration should match the initial guess
#[test]
fn frozen_entry_test() {
let gram = {
let mut gram_to_be = PartialMatrix::new();
for j in 0..2 {
for k in j..2 {
gram_to_be.push_sym(j, k, if (j, k) == (1, 1) { 1.0 } else { 0.0 });
}
}
gram_to_be
};
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), (3, 1)];
println!();
let (config, success, history) = realize_gram(
&gram, guess.clone(), &frozen,
1.0e-12, 0.5, 0.9, 1.1, 200, 110
);
assert_eq!(success, true);
for base_step in history.base_step.into_iter() {
for index in frozen {
assert_eq!(base_step[index], 0.0);
}
}
for index in frozen {
assert_eq!(config[index], guess[index]);
}
}
}

View File

@ -8,14 +8,14 @@ use rustc_hash::FxHashSet;
use sycamore::prelude::*; use sycamore::prelude::*;
use add_remove::AddRemove; use add_remove::AddRemove;
use assembly::Assembly; use assembly::{Assembly, ElementKey};
use display::Display; use display::Display;
use outline::Outline; use outline::Outline;
#[derive(Clone)] #[derive(Clone)]
struct AppState { struct AppState {
assembly: Assembly, assembly: Assembly,
selection: Signal<FxHashSet<usize>> selection: Signal<FxHashSet<ElementKey>>
} }
impl AppState { impl AppState {

View File

@ -1,12 +1,40 @@
use itertools::Itertools; use itertools::Itertools;
use sycamore::{prelude::*, web::tags::div}; use sycamore::{prelude::*, web::tags::div};
use web_sys::{Element, KeyboardEvent, MouseEvent, wasm_bindgen::JsCast}; use web_sys::{
Element,
Event,
HtmlInputElement,
KeyboardEvent,
MouseEvent,
wasm_bindgen::JsCast
};
use crate::AppState; use crate::{AppState, assembly::Constraint};
// this component lists the elements of the assembly, showing the constraints // an editable view of the Lorentz product representing a constraint
// on each element as a collapsible sub-list. its implementation is based on #[component(inline_props)]
// Kate Morley's HTML + CSS tree views: fn LorentzProductInput(constraint: Constraint) -> View {
view! {
input(
r#type="text",
bind:value=constraint.lorentz_prod_text,
on:change=move |event: Event| {
let target: HtmlInputElement = event.target().unwrap().unchecked_into();
match target.value().parse::<f64>() {
Ok(lorentz_prod) => batch(|| {
constraint.lorentz_prod.set(lorentz_prod);
constraint.lorentz_prod_valid.set(true);
}),
Err(_) => constraint.lorentz_prod_valid.set(false)
};
}
)
}
}
// 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/ // https://iamkate.com/code/tree-views/
// //
@ -44,15 +72,13 @@ pub fn Outline() -> View {
} }
}); });
let label = elt.label.clone(); let label = elt.label.clone();
let rep_components = elt.rep.iter().map(|u| { let rep_components = elt.representation.iter().map(|u| {
let u_coord = u.to_string().replace("-", "\u{2212}"); let u_coord = u.to_string().replace("-", "\u{2212}");
View::from(div().children(u_coord)) View::from(div().children(u_coord))
}).collect::<Vec<_>>(); }).collect::<Vec<_>>();
let constrained = elt.constraints.len() > 0; let constrained = elt.constraints.len() > 0;
let details_node = create_node_ref(); let details_node = create_node_ref();
view! { view! {
/* [TO DO] switch to integer-valued parameters whenever
that becomes possible again */
li { li {
details(ref=details_node) { details(ref=details_node) {
summary( summary(
@ -124,21 +150,21 @@ pub fn Outline() -> View {
ul(class="constraints") { ul(class="constraints") {
Keyed( Keyed(
list=elt.constraints.into_iter().collect::<Vec<_>>(), list=elt.constraints.into_iter().collect::<Vec<_>>(),
view=move |c_key: usize| { view=move |c_key| {
let c_state = use_context::<AppState>(); let c_state = use_context::<AppState>();
let assembly = &c_state.assembly; let assembly = &c_state.assembly;
let cst = assembly.constraints.with(|csts| csts[c_key].clone()); let cst = assembly.constraints.with(|csts| csts[c_key].clone());
let other_arg = if cst.args.0 == key { let other_arg = if cst.subjects.0 == key {
cst.args.1 cst.subjects.1
} else { } else {
cst.args.0 cst.subjects.0
}; };
let other_arg_label = assembly.elements.with(|elts| elts[other_arg].label.clone()); let other_arg_label = assembly.elements.with(|elts| elts[other_arg].label.clone());
view! { view! {
li(class="cst") { li(class="cst") {
input(r#type="checkbox", bind:checked=cst.active) input(r#type="checkbox", bind:checked=cst.active)
div(class="cst-label") { (other_arg_label) } div(class="cst-label") { (other_arg_label) }
div(class="cst-rep") { (cst.rep) } LorentzProductInput(constraint=cst)
} }
} }
}, },

View File

@ -8,7 +8,8 @@ using Optim
export export
rand_on_shell, Q, DescentHistory, 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 === # === guessing ===
@ -143,7 +144,7 @@ function realize_gram_gradient(
break break
end end
# find negative gradient of loss function # find the negative gradient of the loss function
neg_grad = 4*Q*L*Δ_proj neg_grad = 4*Q*L*Δ_proj
slope = norm(neg_grad) slope = norm(neg_grad)
dir = neg_grad / slope dir = neg_grad / slope
@ -232,7 +233,7 @@ function realize_gram_newton(
break break
end end
# find the negative gradient of loss function # find the negative gradient of the loss function
neg_grad = 4*Q*L*Δ_proj neg_grad = 4*Q*L*Δ_proj
# find the negative Hessian of the loss function # find the negative Hessian of the loss function
@ -313,6 +314,129 @@ function realize_gram_optim(
) )
end 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 # 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` # explicit entry of `gram`. use gradient descent starting from `guess`
function realize_gram( function realize_gram(
@ -321,7 +445,6 @@ function realize_gram(
frozen = nothing; frozen = nothing;
scaled_tol = 1e-30, scaled_tol = 1e-30,
min_efficiency = 0.5, min_efficiency = 0.5,
init_rate = 1.0,
backoff = 0.9, backoff = 0.9,
reg_scale = 1.1, reg_scale = 1.1,
max_descent_steps = 200, max_descent_steps = 200,
@ -352,20 +475,19 @@ function realize_gram(
unfrozen_stacked = reshape(is_unfrozen, total_dim) unfrozen_stacked = reshape(is_unfrozen, total_dim)
end end
# initialize variables # initialize search state
grad_rate = init_rate
L = copy(guess) L = copy(guess)
# use Newton's method with backtracking and gradient descent backup
Δ_proj = proj_diff(gram, L'*Q*L) Δ_proj = proj_diff(gram, L'*Q*L)
loss = dot(Δ_proj, Δ_proj) loss = dot(Δ_proj, Δ_proj)
# use Newton's method with backtracking and gradient descent backup
for step in 1:max_descent_steps for step in 1:max_descent_steps
# stop if the loss is tolerably low # stop if the loss is tolerably low
if loss < tol if loss < tol
break break
end end
# find the negative gradient of loss function # find the negative gradient of the loss function
neg_grad = 4*Q*L*Δ_proj neg_grad = 4*Q*L*Δ_proj
# find the negative Hessian of the loss function # find the negative Hessian of the loss function
@ -420,6 +542,7 @@ function realize_gram(
empty!(history.last_line_loss) empty!(history.last_line_loss)
rate = one(T) rate = one(T)
step_success = false step_success = false
base_target_improvement = dot(neg_grad, base_step)
for backoff_steps in 0:max_backoff_steps for backoff_steps in 0:max_backoff_steps
history.stepsize[end] = rate history.stepsize[end] = rate
L = L_last + rate * base_step L = L_last + rate * base_step
@ -428,7 +551,7 @@ function realize_gram(
improvement = loss_last - loss improvement = loss_last - loss
push!(history.last_line_L, L) push!(history.last_line_L, L)
push!(history.last_line_loss, loss / scale_adjustment) 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 history.backoff_steps[end] = backoff_steps
step_success = true step_success = true
break break

View File

@ -75,3 +75,12 @@ if success
println(" ", 1 / L[4,k], " sun") println(" ", 1 / L[4,k], " sun")
end end
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")

View File

@ -65,3 +65,12 @@ else
end end
println("Steps: ", size(history.scaled_loss, 1)) println("Steps: ", size(history.scaled_loss, 1))
println("Loss: ", history.scaled_loss[end], "\n") 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")

View File

@ -94,3 +94,12 @@ if success
radius_ratio = dot(infty, Engine.Q * L[:,5]) / dot(infty, Engine.Q * L[:,6]) radius_ratio = dot(infty, Engine.Q * L[:,5]) / dot(infty, Engine.Q * L[:,6])
println("\nCircumradius / inradius: ", radius_ratio) println("\nCircumradius / inradius: ", radius_ratio)
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")

View File

@ -41,3 +41,25 @@ I will have to work out formulas for the Euclidean distance between two entities
In this vein, it seems as though if J1 and J2 are the reps of two points, then Q(J1,J2) = d^2/2. So then the sphere centered at J1 through J2 is (J1-(2Q(J1,J2),0,0,0,0))/sqrt(2Q(J1,J2)). Ugh has a sqrt in it. Similarly for sphere centered at J3 through J2, (J3-(2Q(J3,J2),0000))/sqrt(2Q(J3,J2)). J1,J2,J3 are collinear if these spheres are tangent, i.e. if those vectors have Q-inner-product 1, which is to say Q(J1,J3) - Q(J1,J2) - Q(J3,J2) = 2sqrt(Q(J1,J2)Q(J2,J3)). But maybe that's not the simplest way of putting it. After all, we can just say that the cross-product of the two differences is 0; that has no square roots in it. In this vein, it seems as though if J1 and J2 are the reps of two points, then Q(J1,J2) = d^2/2. So then the sphere centered at J1 through J2 is (J1-(2Q(J1,J2),0,0,0,0))/sqrt(2Q(J1,J2)). Ugh has a sqrt in it. Similarly for sphere centered at J3 through J2, (J3-(2Q(J3,J2),0000))/sqrt(2Q(J3,J2)). J1,J2,J3 are collinear if these spheres are tangent, i.e. if those vectors have Q-inner-product 1, which is to say Q(J1,J3) - Q(J1,J2) - Q(J3,J2) = 2sqrt(Q(J1,J2)Q(J2,J3)). But maybe that's not the simplest way of putting it. After all, we can just say that the cross-product of the two differences is 0; that has no square roots in it.
One conceivable way to canonicalize lines is to use the *perpendicular* plane that goes through the origin, that's uniquely defined, and anyway just amounts to I = (0,0,d) where d is the ordinary direction vector of the line; and a point J in that plane that the line goes through, which just amounts to J=(r^2,1,E) with Q(I,J) = 0, i.e. E\dot d = 0. It's also the point on the line closest to the origin. The reason that we don't usually use that point as the companion to the direction vector is that the resulting set of six coordinates is not homogeneous. But here that's not an issue, since we have our standard point coordinates and plane coordinates; and for a plane through the origin, only two of the direction coordinates are really free, and then we have the one dot-product relation, so only two of the point coordinates are really free, giving us the correct dimensionality of 4 for the set of lines. So in some sense this says that we could take naively as coordinates for a line the projection of the unit direction vector to the xy plane and the projection of the line's closest point to the origin to the xy plane. That doesn't seem to have any weird gimbal locks or discontinuities or anything. And with these coordinates, you can test if the point E=x,y,z is on the line (dx,dy,cx,cy) by extending (dx,dy) to d via dz = sqrt(1-dx^2 - dy^2), extending (cx,cy) to c by determining cz via d\dot c = 0, and then checking if d\cross(E-c) = 0. And you can see if two lines are parallel just by checking if they have the same direction vector, and if not, you can see if they are coplanar by projecting both of their closest points perpendicularly onto the line in the direction of the cross product of their directions, and if the projections match they are coplanar. One conceivable way to canonicalize lines is to use the *perpendicular* plane that goes through the origin, that's uniquely defined, and anyway just amounts to I = (0,0,d) where d is the ordinary direction vector of the line; and a point J in that plane that the line goes through, which just amounts to J=(r^2,1,E) with Q(I,J) = 0, i.e. E\dot d = 0. It's also the point on the line closest to the origin. The reason that we don't usually use that point as the companion to the direction vector is that the resulting set of six coordinates is not homogeneous. But here that's not an issue, since we have our standard point coordinates and plane coordinates; and for a plane through the origin, only two of the direction coordinates are really free, and then we have the one dot-product relation, so only two of the point coordinates are really free, giving us the correct dimensionality of 4 for the set of lines. So in some sense this says that we could take naively as coordinates for a line the projection of the unit direction vector to the xy plane and the projection of the line's closest point to the origin to the xy plane. That doesn't seem to have any weird gimbal locks or discontinuities or anything. And with these coordinates, you can test if the point E=x,y,z is on the line (dx,dy,cx,cy) by extending (dx,dy) to d via dz = sqrt(1-dx^2 - dy^2), extending (cx,cy) to c by determining cz via d\dot c = 0, and then checking if d\cross(E-c) = 0. And you can see if two lines are parallel just by checking if they have the same direction vector, and if not, you can see if they are coplanar by projecting both of their closest points perpendicularly onto the line in the direction of the cross product of their directions, and if the projections match they are coplanar.
#### Engine Conventions
The coordinate conventions used in the engine are different from the ones used in these notes. Marking the engine vectors and coordinates with $'$, we have
$$I' = (x', y', z', b', c'),$$
where
$$
\begin{align*}
x' & = x & b' & = b/2 \\
y' & = y & c' & = c/2. \\
z' & = z
\end{align*}
$$
The engine uses the quadratic form $Q' = -Q$, which is expressed in engine coordinates as
$$Q'(I'_1, I'_2) = x'_1 x'_2 + y'_1 y'_2 + z'_1 z'_2 - 2(b'_1c'_2 + c'_1 b'_2).$$
In the `engine` module, the matrix of $Q'$ is encoded in the lazy static variable `Q`.
In the engine's coordinate conventions, a sphere with radius $r > 0$ centered on $P = (P_x, P_y, P_z)$ is represented by the vector
$$I'_s = \left(\frac{P_x}{r}, \frac{P_y}{r}, \frac{P_z}{r}, \frac1{2r}, \frac{\|P\|^2 - r^2}{2r}\right),$$
which has the normalization $Q'(I'_s, I'_s) = 1$. The point $P$ is represented by the vector
$$I'_P = \left(P_x, P_y, P_z, \frac{1}{2}, \frac{\|P\|^2}{2}\right).$$
In the `engine` module, these formulas are encoded in the `sphere` and `point` functions.