compb-dla-model/src/system/spaces/continuous.rs

107 lines
2.6 KiB
Rust

use std::f32::consts::PI;
use std::ops::Add;
use bevy::utils::tracing::Instrument;
use kiddo::distance::squared_euclidean;
use kiddo::ErrorKind;
use nalgebra::{DimAdd, Point3};
use rand::Rng;
use serde::Serialize;
use crate::system::sticker::Sticker;
use crate::system::{Position, Storage};
use crate::system::walker::Walker;
#[derive(Serialize, Debug, Clone)]
pub struct P3 {
x: f32,
y: f32,
z: f32,
}
impl P3 {
fn as_arr(&self) -> [f32; 3] {
[self.x, self.y, self.z]
}
pub fn random_with_radius<R: Rng>(rng: &mut R, radius: f32) -> P3 {
let theta = rng.gen_range(0f32..1.0) * 2.0 * PI;
let phi = rng.gen_range(0f32..1.0) * 2.0 * PI;
let (x, y, z) = (
radius * theta.sin() * phi.cos(),
radius * theta.sin() * phi.sin(),
radius * theta.cos()
);
P3 { x, y, z}
}
}
impl Add for P3 {
type Output = P3;
fn add(self, rhs: Self) -> Self::Output {
P3 {
x: self.x + rhs.x,
y: self.y + rhs.y,
z: self.z + rhs.z,
}
}
}
const BALL_RADIUS_SQ: f32 = 1.0;
pub struct ContinuousStorage {
pub inner: kiddo::KdTree<f32, (), 3>,
}
impl Position for P3 {
const DIM: usize = 3;
fn zero() -> Self {
P3 { x: 0f32, y: 0f32, z: 0f32 }
}
fn abs(&self) -> f32 {
(self.x.powi(2) + self.y.powi(2) + self.z.powi(2)).powf(0.5)
}
fn from_cartesian(cartesian: [f32; Self::DIM]) -> Self {
P3 { x: cartesian[0], y: cartesian[1], z: cartesian[3] }
}
}
impl Storage<P3> for ContinuousStorage {
fn is_occupied(&self, position: &P3) -> bool {
let (dist_sq, _) = self.inner.nearest_one(&position.as_arr(), &squared_euclidean).unwrap();
// Is the distance of this point to the next one less than twice the ball radius
dist_sq < 2.0 * BALL_RADIUS_SQ
}
fn deposit(&mut self, position: &P3) {
self.inner.add(&position.as_arr(), ()).expect("Failed to write to space")
}
}
pub struct ContinuousSticker {
/// INVARIANT: THIS SHOULD BE GREATER THAN THE BALL_RADIUS_SQ value
pub range_sq: f32,
}
impl Sticker<P3, ContinuousStorage> for ContinuousSticker {
fn should_stick<R: Rng>(&self, _rng: &mut R, space: &ContinuousStorage, position: &P3) -> bool {
let (a, _) = space.inner.nearest_one(&position.as_arr(), &squared_euclidean).unwrap();
a < self.range_sq
}
}
pub struct ContinuousWalker {
pub walk_step: f32
}
impl Walker<P3> for ContinuousWalker {
fn walk<R: Rng>(&self, rng: &mut R, position: &P3) -> P3 {
position.clone() + P3::random_with_radius(rng, self.walk_step)
}
}