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4 Commits

Author SHA1 Message Date
7216fd561e A great re-architecture of the cli
Some checks failed
continuous-integration/drone/push Build is failing
2023-03-08 16:16:44 +00:00
eceb067add Stash a maybe working mess 2023-03-08 15:08:54 +00:00
c707a20a75 Quite a mess 2023-03-06 12:14:21 +00:00
15c2edde67 Achieve the final result of entirely generic!! 2023-03-05 10:59:08 +00:00
23 changed files with 60911 additions and 353 deletions

171
Cargo.lock generated
View File

@ -1931,6 +1931,20 @@ dependencies = [
"wasm-bindgen",
]
[[package]]
name = "kd-tree"
version = "0.5.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "f54287107c30b23cf7a32e394c68b9472220a090c897d916dfdf467caef88864"
dependencies = [
"nalgebra 0.31.4",
"num-traits",
"ordered-float",
"paste",
"pdqselect",
"typenum",
]
[[package]]
name = "khronos-egl"
version = "4.1.0"
@ -1942,6 +1956,15 @@ dependencies = [
"pkg-config",
]
[[package]]
name = "kiddo"
version = "0.2.5"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "06ced2e69cfc5f22f86ccc9ce4ecff9f19917f3083a4bac0f402bdab034d73f1"
dependencies = [
"num-traits",
]
[[package]]
name = "kqueue"
version = "1.0.7"
@ -2063,6 +2086,15 @@ dependencies = [
"regex-automata",
]
[[package]]
name = "matrixmultiply"
version = "0.3.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "add85d4dd35074e6fedc608f8c8f513a3548619a9024b751949ef0e8e45a4d84"
dependencies = [
"rawpointer",
]
[[package]]
name = "memchr"
version = "2.5.0"
@ -2141,6 +2173,60 @@ dependencies = [
"unicode-xid",
]
[[package]]
name = "nalgebra"
version = "0.31.4"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "20bd243ab3dbb395b39ee730402d2e5405e448c75133ec49cc977762c4cba3d1"
dependencies = [
"approx",
"matrixmultiply",
"nalgebra-macros 0.1.0",
"num-complex",
"num-rational",
"num-traits",
"simba 0.7.3",
"typenum",
]
[[package]]
name = "nalgebra"
version = "0.32.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "d68d47bba83f9e2006d117a9a33af1524e655516b8919caac694427a6fb1e511"
dependencies = [
"approx",
"matrixmultiply",
"nalgebra-macros 0.2.0",
"num-complex",
"num-rational",
"num-traits",
"simba 0.8.0",
"typenum",
]
[[package]]
name = "nalgebra-macros"
version = "0.1.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "01fcc0b8149b4632adc89ac3b7b31a12fb6099a0317a4eb2ebff574ef7de7218"
dependencies = [
"proc-macro2",
"quote",
"syn",
]
[[package]]
name = "nalgebra-macros"
version = "0.2.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "d232c68884c0c99810a5a4d333ef7e47689cfd0edc85efc9e54e1e6bf5212766"
dependencies = [
"proc-macro2",
"quote",
"syn",
]
[[package]]
name = "nd_array"
version = "0.1.0"
@ -2295,6 +2381,15 @@ dependencies = [
"winapi",
]
[[package]]
name = "num-complex"
version = "0.4.3"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "02e0d21255c828d6f128a1e41534206671e8c3ea0c62f32291e808dc82cff17d"
dependencies = [
"num-traits",
]
[[package]]
name = "num-derive"
version = "0.3.3"
@ -2414,6 +2509,15 @@ version = "1.17.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "b7e5500299e16ebb147ae15a00a942af264cf3688f47923b8fc2cd5858f23ad3"
[[package]]
name = "ordered-float"
version = "3.4.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "d84eb1409416d254e4a9c8fa56cc24701755025b458f0fcd8e59e1f5f40c23bf"
dependencies = [
"num-traits",
]
[[package]]
name = "os_str_bytes"
version = "6.4.1"
@ -2464,6 +2568,18 @@ dependencies = [
"windows-sys 0.45.0",
]
[[package]]
name = "paste"
version = "1.0.12"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "9f746c4065a8fa3fe23974dd82f15431cc8d40779821001404d10d2e79ca7d79"
[[package]]
name = "pdqselect"
version = "0.1.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "7778906d9321dd56cde1d1ffa69a73e59dcf5fda6d366f62727adf2bd4193aee"
[[package]]
name = "peeking_take_while"
version = "0.1.2"
@ -2643,6 +2759,12 @@ dependencies = [
"cty",
]
[[package]]
name = "rawpointer"
version = "0.2.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "60a357793950651c4ed0f3f52338f53b2f809f32d83a07f72909fa13e4c6c1e3"
[[package]]
name = "rectangle-pack"
version = "0.4.2"
@ -2719,10 +2841,14 @@ dependencies = [
"cbindgen",
"clap 4.1.8",
"csv",
"kd-tree",
"kiddo",
"nalgebra 0.32.2",
"nd_array",
"num-integer",
"rand",
"serde",
"serde_json",
]
[[package]]
@ -2760,6 +2886,15 @@ version = "1.0.12"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "7b4b9743ed687d4b4bcedf9ff5eaa7398495ae14e61cba0a295704edbc7decde"
[[package]]
name = "safe_arch"
version = "0.6.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "794821e4ccb0d9f979512f9c1973480123f9bd62a90d74ab0f9426fcf8f4a529"
dependencies = [
"bytemuck",
]
[[package]]
name = "same-file"
version = "1.0.6"
@ -2857,6 +2992,32 @@ version = "1.1.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "43b2853a4d09f215c24cc5489c992ce46052d359b5109343cbafbf26bc62f8a3"
[[package]]
name = "simba"
version = "0.7.3"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "2f3fd720c48c53cace224ae62bef1bbff363a70c68c4802a78b5cc6159618176"
dependencies = [
"approx",
"num-complex",
"num-traits",
"paste",
"wide",
]
[[package]]
name = "simba"
version = "0.8.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "50582927ed6f77e4ac020c057f37a268fc6aebc29225050365aacbb9deeeddc4"
dependencies = [
"approx",
"num-complex",
"num-traits",
"paste",
"wide",
]
[[package]]
name = "slab"
version = "0.4.8"
@ -3414,6 +3575,16 @@ dependencies = [
"bitflags",
]
[[package]]
name = "wide"
version = "0.7.8"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "b689b6c49d6549434bf944e6b0f39238cf63693cb7a147e9d887507fffa3b223"
dependencies = [
"bytemuck",
"safe_arch",
]
[[package]]
name = "winapi"
version = "0.3.9"

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@ -38,6 +38,10 @@ num-integer = "0.1.45"
rand = { version = "0.8.5", features = ["default", "small_rng"] }
csv = "1.1"
serde = { version = "1.0.152", features = ["derive"] }
serde_json = "1.0.93"
kd-tree = { version = "0.5.1", features = ["nalgebra"] }
nalgebra = "0.32.2"
kiddo = "0.2.5"
[build-dependencies]
cbindgen = "0.24.3"

10002
balls.json Normal file

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50002
out.json Normal file

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56
src/cli/cli.rs Normal file
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@ -0,0 +1,56 @@
use std::path::PathBuf;
use clap::{Parser, Args, Subcommand, ValueEnum};
#[derive(ValueEnum, Clone, Debug, Copy)]
pub enum OutputFormat {
FullDataJson,
Positions,
}
#[derive(Args, Debug)]
pub struct InitialCli {
pub grid_size: u32
}
#[derive(Args, Debug)]
pub struct StickProbabilityCli {
pub grid_size: u32,
pub stick_probability: f32,
}
#[derive(Args, Debug)]
pub struct BallsCli {
pub ball_radius: f32,
pub stick_distance: f32,
pub walk_step: f32,
}
#[derive(Subcommand, Debug)]
pub enum PCM {
Initial(InitialCli),
StickProbability(StickProbabilityCli),
Grid3(StickProbabilityCli),
Hex(StickProbabilityCli),
Balls(BallsCli)
}
#[derive(Parser, Debug)]
pub struct ModelCli {
#[command(subcommand)]
pub preconfigured_model: PCM,
#[arg(long)]
pub max_frames: Option<usize>,
#[arg(short = 'N', long)]
pub max_particles: usize,
#[arg(long, short)]
pub seed: u64,
#[arg(value_enum, short, long, default_value_t = OutputFormat::Positions)]
pub format: OutputFormat,
#[arg(value_enum, short, long)]
pub output: PathBuf,
}

24
src/cli/mod.rs Normal file
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@ -0,0 +1,24 @@
use rand::Rng;
use crate::system::model::DLASystem;
use crate::system::{Position, Storage};
use crate::system::spawner::Spawner;
use crate::system::sticker::Sticker;
use crate::system::walker::Walker;
pub mod cli;
pub mod output;
pub fn drive_system<R: Rng, P: Position, S: Storage<P>, W: Walker<P>, Sp: Spawner<P>, St: Sticker<P, S>>(sys: &mut DLASystem<R, P, S, W, Sp, St>, max_frames: Option<usize>) {
while sys.running {
sys.update();
match max_frames {
Some(max_frames) if max_frames <= sys.frame => {
sys.running = false;
eprintln!("System halted as it ran to {frame} frames (max_frames = {max_frames}) and did not complete", frame = sys.frame)
}
_ => {}
}
}
}

49
src/cli/output.rs Normal file
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@ -0,0 +1,49 @@
use std::fs::File;
use std::path::Path;
use rand::Rng;
use crate::cli::cli::OutputFormat;
use crate::system::model::DLASystem;
use crate::system::{Position, Storage};
use crate::system::spawner::Spawner;
use crate::system::sticker::Sticker;
use crate::system::walker::Walker;
pub fn write<R: Rng, P: Position, S: Storage<P>, W: Walker<P>, Sp: Spawner<P>, St: Sticker<P, S>>(
sys: &DLASystem<R, P, S, W, Sp, St>,
format: OutputFormat,
output: &Path,
) {
match format {
OutputFormat::FullDataJson => write_json_full_data(sys, output),
OutputFormat::Positions => write_csv_positions(sys, output),
}
}
fn write_csv_positions<R: Rng, P: Position, S: Storage<P>, W: Walker<P>, Sp: Spawner<P>, St: Sticker<P, S>>(sys: &DLASystem<R, P, S, W, Sp, St>, csv_path: &Path) {
let mut wtr = csv::Writer::from_path(csv_path)
.expect("Failed to open file");
// CSVs can only store the raw positions
let positions: Vec<&P> = sys.history
.iter()
.map(|line| &line.position)
.collect();
wtr.serialize(positions)
.unwrap();
wtr.flush()
.unwrap();
}
fn write_json_full_data<R: Rng, P: Position, S: Storage<P>, W: Walker<P>, Sp: Spawner<P>, St: Sticker<P, S>>(sys: &DLASystem<R, P, S, W, Sp, St>, output_path: &Path) {
let file = File::create(output_path).expect("Failed to open file");
let vec: Vec<P> = sys.history
.iter()
.map(|l| l.position.clone())
.collect();
serde_json::to_writer(file, &vec)
.expect("Failed to write json");
}

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@ -1,7 +1,7 @@
#![feature(array_zip)]
use system::Storage;
use crate::system::grid::{Position, VectorStorage};
use crate::system::grid::{Pos2D, VectorStorage};
mod system;
@ -19,12 +19,12 @@ pub extern "C" fn storage_new(grid_size: u32) -> &'static mut CStorage {
#[no_mangle]
pub extern "C" fn storage_at(storage: &CStorage, i: i32, j: i32) -> bool {
storage.0.at(&Position { x: i, y: j })
storage.0.at(&Pos2D { x: i, y: j })
}
#[no_mangle]
pub extern "C" fn storage_deposit(storage: &mut CStorage, i: i32, j: i32, val: u8) {
storage.0.write(&Position { x: i, y: j }, val == 1);
storage.0.write(&Pos2D { x: i, y: j }, val == 1);
}
#[no_mangle]
@ -35,7 +35,7 @@ pub extern "C" fn walk(d: u32, i: i32, j: i32) -> CPosition {
mod test {
use num_integer::Integer;
use crate::CPosition;
use crate::system::grid::Position;
use crate::system::grid::Pos2D;
pub(crate) fn a(d: u32, i: i32, j: i32) -> CPosition {
match d {
@ -51,8 +51,8 @@ mod test {
let (dim, sign) = d.div_rem(&2);
let sign = if sign == 0 { 1 } else { -1 };
// HACK: Our conventin and the MVA are different, since we are trying to strangle fig this, quick hack.
let offset = Position::in_direction(dim, sign);
let next = Position { x: i, y: j } + offset;
let offset = Pos2D::in_direction(dim, sign);
let next = Pos2D { x: i, y: j } + offset;
CPosition(next.x, next.y)
}

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@ -1,47 +0,0 @@
use std::path::Path;
use rand::rngs::SmallRng;
use rand::{Rng, SeedableRng};
use crate::system::grid::{Position, VectorStorage};
use crate::system::model::DLASystem;
use crate::system::nd::{NDPosition, NDVectorStorage};
use crate::system::{GriddedPosition, Storage};
use crate::system::walker::{LocalRandomWalker, Walker};
pub fn execute<R: Rng, P: GriddedPosition, S: Storage<P>, W: Walker<P>>(sys: &mut DLASystem<R, P, S, W>, csv_path: &Path) {
while sys.running {
sys.update();
}
sys.export_data(csv_path)
.expect("Failed to write");
}
pub fn initial_config(seed: u64, max_particles: usize) -> DLASystem<SmallRng, Position, VectorStorage, LocalRandomWalker> {
DLASystem::new_g(
SmallRng::seed_from_u64(seed),
VectorStorage::new(1600),
LocalRandomWalker,
1.0,
max_particles,
)
}
pub fn stick_probability(seed: u64, max_particles: usize, stick_probability: f32) -> DLASystem<SmallRng, Position, VectorStorage, LocalRandomWalker> {
DLASystem::new_g(
SmallRng::seed_from_u64(seed),
VectorStorage::new(1600),
LocalRandomWalker,
stick_probability,
max_particles,
)
}
pub fn three_dimensional(seed: u64, max_particles: usize, stick_probability: f32) -> DLASystem<SmallRng, NDPosition<3>, NDVectorStorage<3>, LocalRandomWalker> {
DLASystem::new_g(
SmallRng::seed_from_u64(seed),
NDVectorStorage::new(1600),
LocalRandomWalker,
stick_probability,
max_particles,
)
}

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@ -1,51 +1,98 @@
#![feature(array_zip)]
use std::path::PathBuf;
mod system;
mod example_systems;
#![feature(generic_const_exprs)]
use clap::Parser;
use crate::example_systems::{execute, stick_probability, three_dimensional};
use rand::prelude::*;
use crate::cli::{drive_system};
use crate::cli::cli::{StickProbabilityCli, InitialCli, BallsCli, PCM, ModelCli};
use crate::cli::output::write;
use crate::system::model::DLASystem;
use crate::system::spaces::continuous::{ContinuousSticker, ContinuousStorage, ContinuousWalker};
use crate::system::spaces::hexagonal::HexPosition;
use crate::system::spaces::square_grid::{Grid2D, Grid3D};
use crate::system::spaces::VectorStorage;
use crate::system::spawner::UniformSpawner;
use crate::system::sticker::{ProbabilisticSticking, SimpleSticking};
use crate::system::walker::LocalRandomWalker;
#[derive(Parser, Debug)]
struct Cli {
#[arg(short, long, default_value_t = 2)]
dim: u32,
seed: u64,
max_particles: usize,
stick_probability: f32,
csv_path: PathBuf,
}
mod system;
mod surface_probability_measure;
mod cli;
fn main() {
let cli = Cli::parse();
let cli = ModelCli::parse();
println!("Running: {:?}", cli);
match cli.dim {
2 => {
let mut sys = stick_probability(
cli.seed,
match cli.preconfigured_model {
PCM::Initial(InitialCli { grid_size }) => {
let mut sys = DLASystem::<_, Grid2D, _, _, _, _>::new(
SmallRng::seed_from_u64(cli.seed),
VectorStorage::new(grid_size, 2),
LocalRandomWalker,
UniformSpawner,
SimpleSticking,
cli.max_particles,
cli.stick_probability,
);
execute(&mut sys, &cli.csv_path);
},
drive_system(&mut sys, cli.max_frames);
write(&sys, cli.format, &cli.output);
}
3 => {
let mut sys = three_dimensional(
cli.seed,
PCM::StickProbability(StickProbabilityCli { grid_size, stick_probability }) => {
let mut sys = DLASystem::<_, Grid2D, _, _, _, _>::new(
SmallRng::seed_from_u64(cli.seed),
VectorStorage::new(grid_size, 2),
LocalRandomWalker,
UniformSpawner,
ProbabilisticSticking { stick_probability },
cli.max_particles,
cli.stick_probability,
);
execute(&mut sys, &cli.csv_path);
},
drive_system(&mut sys, cli.max_frames);
write(&sys, cli.format, &cli.output);
}
n => panic!("Model not compiled with {n} dimensional support")
PCM::Grid3(StickProbabilityCli { grid_size, stick_probability }) => {
let mut sys = DLASystem::<_, Grid3D, _, _, _, _>::new(
SmallRng::seed_from_u64(cli.seed),
VectorStorage::new(grid_size, 3),
LocalRandomWalker,
UniformSpawner,
ProbabilisticSticking { stick_probability },
cli.max_particles,
);
drive_system(&mut sys, cli.max_frames);
write(&sys, cli.format, &cli.output);
}
PCM::Hex(StickProbabilityCli { grid_size, stick_probability }) => {
let mut sys = DLASystem::<_, HexPosition, _, _, _, _>::new(
SmallRng::seed_from_u64(cli.seed),
VectorStorage::new(grid_size, 2),
LocalRandomWalker,
UniformSpawner,
ProbabilisticSticking { stick_probability },
cli.max_particles,
);
drive_system(&mut sys, cli.max_frames);
write(&sys, cli.format, &cli.output);
}
PCM::Balls(BallsCli { ball_radius, stick_distance, walk_step }) => {
let mut sys = DLASystem::new(
SmallRng::seed_from_u64(cli.seed),
ContinuousStorage { inner: kiddo::KdTree::new(), ball_radius_sq: ball_radius * ball_radius },
ContinuousWalker { walk_step },
UniformSpawner,
ContinuousSticker { range_sq: stick_distance * stick_distance },
cli.max_particles,
);
drive_system(&mut sys, cli.max_frames);
write(&sys, cli.format, &cli.output);
}
}
}

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@ -0,0 +1,54 @@
use std::fs::File;
use std::path::Path;
use bevy::render::render_resource::AsBindGroupShaderType;
use kd_tree::KdTree;
use rand::rngs::SmallRng;
use rand::{Rng, SeedableRng};
use crate::system::model::DLASystem;
use crate::system::{Position, Storage};
use crate::system::spaces::continuous::{ContinuousSticker, ContinuousStorage, ContinuousWalker, P3};
use crate::system::spaces::hexagonal::HexPosition;
use crate::system::spaces::square_grid::{Grid2D, Grid3D};
use crate::system::spaces::VectorStorage;
use crate::system::spawner::{Spawner, UniformSpawner};
use crate::system::sticker::{ProbabilisticSticking, SimpleSticking, Sticker};
use crate::system::walker::{LocalRandomWalker, Walker};
struct LoggerSticker {
inner: SimpleSticking
}
impl<S: Storage<Grid2D>> Sticker<Grid2D, S> for LoggerSticker {
fn should_stick<R: Rng>(&self, rng: &mut R, space: &S, position: &Grid2D) -> bool {
if self.inner.should_stick(rng, space, position) {
println!("{:?}", position);
}
false
}
}
struct ReadOnlyVectorStorage {
inner: VectorStorage,
}
impl Storage<Grid2D> for ReadOnlyVectorStorage {
fn is_occupied(&self, position: &Grid2D) -> bool {
self.inner.is_occupied(position)
}
fn deposit(&mut self, position: &Grid2D) {
eprintln!("Write ignore for space at {position:?}");
}
}
pub fn surface_probability_measure(seed: u64, max_particles: usize, stick_probability: f32) -> DLASystem<SmallRng, HexPosition, VectorStorage, LocalRandomWalker, UniformSpawner, ProbabilisticSticking> {
DLASystem::new(
SmallRng::seed_from_u64(seed),
VectorStorage::new(1600, 3),
LocalRandomWalker,
UniformSpawner,
ProbabilisticSticking { stick_probability },
max_particles,
)
}

View File

@ -1,92 +0,0 @@
use std::f32::consts::PI;
use std::ops::Add;
use num_integer::Integer;
use rand::Rng;
use crate::system::{GriddedPosition, Storage};
use serde::{Serialize, Deserialize};
pub struct VectorStorage {
backing: Vec<bool>,
grid_size: u32,
}
#[derive(Clone, Debug, PartialEq, Eq, Serialize, Deserialize)]
pub struct Position {
pub x: i32,
pub y: i32,
}
impl Position {
pub fn in_direction(direction: u32, value: i32) -> Self {
if direction == 0 { Position { x: value, y: 0 } } else { Position { x: 0, y: value } }
}
}
impl Add for Position {
type Output = Position;
fn add(self, rhs: Self) -> Self::Output {
Position { x: self.x + rhs.x, y: self.y + rhs.y }
}
}
impl GriddedPosition for Position {
const NEIGHBOURS: u32 = 4;
fn zero() -> Position {
Position { x: 0, y: 0 }
}
fn spawn<R: Rng>(rng: &mut R, radius: f32) -> Self {
let theta = rng.gen_range(0f32..1.0) * 2.0 * PI;
let (x, y) = (radius * theta.cos(), radius * theta.sin());
Position { x: x as i32, y: y as i32 }
}
fn abs(&self) -> f32 {
((self.x.pow(2) + self.y.pow(2)) as f32).powf(0.5)
}
fn neighbour(&self, neighbour_index: u32) -> Self {
let (dim, sign) = neighbour_index.div_rem(&2);
let sign = if sign == 0 { 1 } else { -1 };
let offset = Position::in_direction(dim, sign);
self.clone() + offset
}
fn linear_index(&self, grid_size: u32) -> usize {
let grid_size = grid_size as i32;
assert!(self.x <= grid_size && -(grid_size) <= self.x);
assert!(self.y <= grid_size && -(grid_size) <= self.y);
let x = (self.x + (grid_size) / 2) as usize;
let y = (self.y + (grid_size) / 2) as usize;
return grid_size as usize * y + x;
}
}
impl VectorStorage {
pub fn new(grid_size: u32) -> VectorStorage {
VectorStorage { grid_size, backing: vec![false; grid_size.pow(2) as usize] }
}
/*
* Convenience function for c-binding
* */
pub fn write(&mut self, position: &Position, val: bool) {
self.backing[position.linear_index(self.grid_size)] = val;
}
}
impl Storage<Position> for VectorStorage {
fn at(&self, position: &Position) -> bool {
return self.backing[position.linear_index(self.grid_size)]
}
fn deposit(&mut self, position: &Position) {
self.backing[position.linear_index(self.grid_size)] = true;
}
}

View File

@ -1,24 +1,28 @@
use std::ops::Add;
use rand::Rng;
use serde::Serialize;
pub mod walker;
pub mod grid;
pub mod spawner;
pub mod sticker;
pub mod model;
pub mod nd;
mod hexagonal;
pub mod spaces;
pub trait GriddedPosition: Add<Output=Self> + Serialize + Clone {
const NEIGHBOURS: u32;
pub trait Position: Add<Output=Self> + Serialize + Clone {
const DIM: usize;
fn zero() -> Self;
fn spawn<R: Rng>(rng: &mut R, radius: f32) -> Self;
fn abs(&self) -> f32;
fn from_cartesian(cartesian: [f32; Self::DIM]) -> Self;
}
pub trait GriddedPosition: Position {
const NEIGHBOURS: u32;
fn neighbour(&self, neighbour_index: u32) -> Self;
fn linear_index(&self, grid_size: u32) -> usize;
}
pub trait Storage<P: GriddedPosition> {
fn at(&self, position: &P) -> bool;
pub trait Storage<P: Position> {
fn is_occupied(&self, position: &P) -> bool;
fn deposit(&mut self, position: &P);
}

View File

@ -1,19 +1,44 @@
use std::io;
use std::path::Path;
use rand::prelude::*;
use crate::system::{GriddedPosition, Storage};
use serde::Serialize;
use crate::system::{Position, Storage};
use crate::system::spawner::Spawner;
use crate::system::sticker::Sticker;
use crate::system::walker::Walker;
pub struct DLASystem<R: Rng, P: GriddedPosition, S: Storage<P>, W: Walker<P>> {
#[derive(Serialize)]
pub struct HistoryLine<P: Position> {
pub frame: usize,
pub cluster_radius: f32,
pub fd: f32,
pub position: P,
}
pub struct DLASystem<R: Rng, P: Position, S: Storage<P>, W: Walker<P>, Sp: Spawner<P>, St: Sticker<P, S>> {
rng: R,
/*
* These object encapsulate the behaviour of our particular model.
*/
/*
* The space, along with the chosen position choose the embedding space that the cluster grows
* in.
*/
space: S,
/*
* Walkers allow us to choose between different particle movement behaviours, eg random or
* biased walker
*/
walker: W,
spawner: Sp,
sticker: St,
stick_probability: f32,
max_particles: usize,
pub frame: usize,
pub running: bool,
pub history: Vec<HistoryLine<P>>,
max_particles: usize,
particles: Vec<P>,
active_particle: Option<P>,
@ -24,17 +49,21 @@ pub struct DLASystem<R: Rng, P: GriddedPosition, S: Storage<P>, W: Walker<P>> {
cluster_radius: f32,
}
impl<R: Rng, P: GriddedPosition, S: Storage<P>, W: Walker<P>> DLASystem<R, P, S, W> {
pub fn new_g(rng: R, space: S, walker: W, stick_probability: f32, max_particles: usize) -> Self {
impl<R: Rng, P: Position, S: Storage<P>, W: Walker<P>, Sp: Spawner<P>, St: Sticker<P, S>> DLASystem<R, P, S, W, Sp, St> {
pub fn new(rng: R, space: S, walker: W, spawner: Sp, sticker: St, max_particles: usize) -> Self {
let mut sys = DLASystem {
rng,
stick_probability,
max_particles,
running: true,
spawner,
sticker,
space,
walker,
frame: 0,
particles: vec![],
history: vec![],
active_particle: None,
add_ratio: 1.2,
@ -51,6 +80,7 @@ impl<R: Rng, P: GriddedPosition, S: Storage<P>, W: Walker<P>> DLASystem<R, P, S,
}
pub fn update(&mut self) {
self.frame += 1;
if self.active_particle.is_some() {
self.move_particle();
} else if self.particles.len() < self.max_particles {
@ -71,8 +101,8 @@ impl<R: Rng, P: GriddedPosition, S: Storage<P>, W: Walker<P>> DLASystem<R, P, S,
if distance > self.kill_circle {
self.active_particle = None;
} else if !self.space.at(&next_position) {
if self.check_stick(&next_position) {
} else if !self.space.is_occupied(&next_position) {
if self.sticker.should_stick(&mut self.rng, &self.space, &next_position) {
self.deposit(&next_position);
self.active_particle = None;
return;
@ -82,19 +112,10 @@ impl<R: Rng, P: GriddedPosition, S: Storage<P>, W: Walker<P>> DLASystem<R, P, S,
}
}
fn check_stick(&mut self, position: &P) -> bool {
(0..P::NEIGHBOURS)
.map(|n| position.neighbour(n))
.any(|neighbour|
self.space.at(&neighbour)
&& self.rng.gen_range(0.0f32..=1.0) < self.stick_probability
)
}
fn spawn_particle(&mut self) {
let position = P::spawn(&mut self.rng, self.add_circle);
let position = self.spawner.spawn(&mut self.rng, self.add_circle);
if !self.space.at(&position) {
if !self.space.is_occupied(&position) {
self.active_particle = Some(position);
}
}
@ -113,16 +134,7 @@ impl<R: Rng, P: GriddedPosition, S: Storage<P>, W: Walker<P>> DLASystem<R, P, S,
self.kill_circle = self.kill_ratio * self.add_circle;
}
}
}
pub fn export_data(&self, path: &Path) -> io::Result<()> {
let mut wtr = csv::Writer::from_path(path)?;
for particle in &self.particles {
wtr.serialize(particle)?;
}
wtr.flush()?;
Ok(())
self.history.push(HistoryLine { frame: self.frame, position: p0.clone(), cluster_radius: self.cluster_radius, fd: (self.particles.len() as f32).ln() / self.cluster_radius.ln() });
}
}

View File

@ -1,107 +0,0 @@
use std::ops::Add;
use num_integer::Integer;
use rand::Rng;
use serde::{Serialize, Serializer};
use serde::ser::{SerializeMap, SerializeSeq, SerializeStruct};
use crate::system::GriddedPosition;
use crate::system::Storage;
pub struct NDVectorStorage<const DIM: usize> {
backing: Vec<bool>,
grid_size: u32,
}
impl<const DIM: usize> NDVectorStorage<DIM> {
pub fn new(grid_size: u32) -> Self {
Self { grid_size, backing: vec![false; grid_size.pow(DIM as u32) as usize] }
}
}
impl<const DIM: usize> Storage<NDPosition<DIM>> for NDVectorStorage<DIM> {
fn at(&self, position: &NDPosition<DIM>) -> bool {
return self.backing[position.linear_index(self.grid_size)];
}
fn deposit(&mut self, position: &NDPosition<DIM>) {
self.backing[position.linear_index(self.grid_size)] = true;
}
}
#[derive(Clone, Debug, PartialEq, Eq)]
pub struct NDPosition<const DIM: usize>([i32; DIM]);
impl<const DIM: usize> NDPosition<DIM> {
pub fn in_direction(direction: usize, value: i32) -> Self {
let mut arr = [0; DIM];
arr[direction] = value;
NDPosition(arr)
}
}
impl<const DIM: usize> Add for NDPosition<DIM> {
type Output = Self;
fn add(self, rhs: Self) -> Self::Output {
Self(self.0.zip(rhs.0).map(|(a, b)| a + b))
}
}
impl<const DIM: usize> Serialize for NDPosition<DIM> {
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error> where S: Serializer {
let mut ser = serializer.serialize_struct("NDPosition", DIM)?;
for (i, v) in self.0.iter().enumerate() {
ser.serialize_field(Box::leak(Box::new(format!("r{i}"))), v)?;
}
ser.end()
}
}
impl<const DIM: usize> GriddedPosition for NDPosition<DIM> {
const NEIGHBOURS: u32 = { 2u32.pow(DIM as u32) } as u32;
fn zero() -> Self {
NDPosition([0; DIM])
}
fn spawn<R: Rng>(rng: &mut R, radius: f32) -> Self {
let mut a: [f32; DIM] = [0f32; DIM];
let mut b: [i32; DIM] = [0i32; DIM];
for i in 0..DIM {
a[i] = rng.gen_range(0f32..1f32);
}
let norm = a.iter().sum::<f32>()
.sqrt();
for i in 0..DIM {
a[i] = a[i] * radius / norm;
b[i] = a[i] as i32;
}
return Self(b);
}
fn abs(&self) -> f32 {
let a: i32 = self.0.iter()
.map(|r| r.pow(2))
.sum();
(a as f32).powf(0.5)
}
fn neighbour(&self, neighbour_index: u32) -> Self {
let (dim, sign) = neighbour_index.div_rem(&(DIM as u32));
let sign = if sign == 0 { 1 } else { -1 };
let offset = Self::in_direction(dim as usize, sign);
self.clone() + offset
}
fn linear_index(&self, grid_size: u32) -> usize {
self.0.iter()
.enumerate()
.map(|(i, v)| (grid_size.pow(i as u32) as usize) * (v + ((grid_size / 2) as i32)) as usize)
.sum()
}
}

View File

@ -0,0 +1,102 @@
use std::f32::consts::PI;
use std::ops::Add;
use kiddo::distance::squared_euclidean;
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,
}
}
}
pub struct ContinuousStorage {
pub inner: kiddo::KdTree<f32, (), 3>,
pub ball_radius_sq: f32,
}
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 * self.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)
}
}

View File

@ -1,6 +1,5 @@
use std::ops::Add;
use rand::Rng;
use crate::system::GriddedPosition;
use crate::system::{GriddedPosition, Position};
use serde::{Serialize, Deserialize};
#[derive(Clone, Debug, PartialEq, Eq, Serialize, Deserialize)]
@ -20,18 +19,6 @@ impl Add for HexPosition {
impl GriddedPosition for HexPosition {
const NEIGHBOURS: u32 = 6;
fn zero() -> Self {
HexPosition { q: 0, r: 0 }
}
fn spawn<R: Rng>(rng: &mut R, radius: f32) -> Self {
todo!()
}
fn abs(&self) -> f32 {
((self.q.pow(2) + self.r.pow(2) + self.q * self.r) as f32).sqrt()
}
fn neighbour(&self, neighbour_index: u32) -> Self {
let neighbour_index = neighbour_index as usize;
@ -44,7 +31,28 @@ impl GriddedPosition for HexPosition {
}
fn linear_index(&self, grid_size: u32) -> usize {
todo!()
// ((self.q + grid_size / 2) + grid_size * self.r) as usize
let q = (self.q + (grid_size as i32 / 2)) as usize;
let r = (self.r + (grid_size as i32 / 2)) as usize;
r * (grid_size as usize) + q
}
}
impl Position for HexPosition {
const DIM: usize = 2;
fn zero() -> Self {
HexPosition { q: 0, r: 0 }
}
fn abs(&self) -> f32 {
((self.q.pow(2) + self.r.pow(2) + self.q * self.r) as f32).sqrt()
}
fn from_cartesian(cartesian: [f32; Self::DIM]) -> Self {
let q = (1.0f32/3.0f32).sqrt() * cartesian[0] - 1.0/3.0 * cartesian[1];
let r = 2.0/3.0 * cartesian[1];
Self { q: q as i32, r: r as i32 }
}
}

7
src/system/spaces/mod.rs Normal file
View File

@ -0,0 +1,7 @@
pub mod vector_storage;
pub use vector_storage::VectorStorage;
pub mod square_grid;
pub mod hexagonal;
pub mod continuous;

View File

@ -0,0 +1,158 @@
use std::ops::Add;
use num_integer::Integer;
use crate::system::{GriddedPosition, Position};
use serde::{Serialize, Deserialize};
#[derive(Clone, Debug, PartialEq, Eq, Serialize, Deserialize)]
pub struct Grid2D {
pub x: i32,
pub y: i32,
}
impl Grid2D {
pub fn in_direction(direction: u32, value: i32) -> Self {
match direction {
0 => Grid2D { x: value, y: 0 },
1 => Grid2D { x: 0, y: value },
_ => panic!("Invalid direction"),
}
}
}
impl Add for Grid2D {
type Output = Grid2D;
fn add(self, rhs: Self) -> Self::Output {
Grid2D { x: self.x + rhs.x, y: self.y + rhs.y }
}
}
impl Position for Grid2D {
const DIM: usize = 2;
fn zero() -> Self {
Grid2D { x: 0, y: 0 }
}
fn abs(&self) -> f32 {
(((self.x * self.x) + (self.y * self.y)) as f32).powf(0.5)
}
fn from_cartesian(cartesian: [f32; Self::DIM]) -> Self {
Grid2D {
x: cartesian[0] as i32,
y: cartesian[1] as i32,
}
}
}
impl GriddedPosition for Grid2D {
const NEIGHBOURS: u32 = 4;
fn neighbour(&self, neighbour_index: u32) -> Self {
let (dim, sign) = neighbour_index.div_rem(&2);
let sign = if sign == 0 { 1 } else { -1 };
let offset = Self::in_direction(dim, sign);
self.clone() + offset
}
fn linear_index(&self, grid_size: u32) -> usize {
let grid_size = grid_size as i32;
assert!(self.x < grid_size && -(grid_size) < self.x);
assert!(self.y < grid_size && -(grid_size) < self.y);
let x = (self.x + (grid_size) / 2) as usize;
let y = (self.y + (grid_size) / 2) as usize;
let linear_index = grid_size as usize * y + x;
if linear_index >= (grid_size * grid_size) as usize {
eprintln!("AHHH SOMETHING WENT WRONG {:?} gives {}", self, linear_index);
}
return linear_index;
}
}
#[derive(Clone, Debug, PartialEq, Eq, Serialize, Deserialize)]
pub struct Grid3D {
pub x: i32,
pub y: i32,
pub z: i32,
}
impl Grid3D {
pub fn in_direction(direction: u32, value: i32) -> Self {
match direction {
0 => Grid3D { x: value, y: 0, z: 0 },
1 => Grid3D { x: 0, y: value, z: 0 },
2 => Grid3D { x: 0, y: 0, z: value },
_ => panic!("Invalid direction"),
}
}
}
impl Add for Grid3D {
type Output = Grid3D;
fn add(self, rhs: Self) -> Self::Output {
Grid3D { x: self.x + rhs.x, y: self.y + rhs.y, z: self.z + rhs.z }
}
}
impl Position for Grid3D {
const DIM: usize = 3;
fn zero() -> Self {
Grid3D { x: 0, y: 0, z: 0 }
}
fn abs(&self) -> f32 {
(((self.x * self.x) + (self.y * self.y) + (self.z * self.z)) as f32).powf(0.5)
}
fn from_cartesian(cartesian: [f32; Self::DIM]) -> Self {
Self {
x: cartesian[0] as i32,
y: cartesian[1] as i32,
z: cartesian[2] as i32,
}
}
}
impl GriddedPosition for Grid3D {
const NEIGHBOURS: u32 = 6;
fn neighbour(&self, neighbour_index: u32) -> Self {
let (dim, sign) = neighbour_index.div_rem(&3);
let sign = if sign == 0 { 1 } else { -1 };
let offset = Self::in_direction(dim, sign);
self.clone() + offset
}
fn linear_index(&self, grid_size: u32) -> usize {
let grid_size = grid_size as i32;
assert!(self.x < grid_size && -(grid_size) < self.x);
assert!(self.y < grid_size && -(grid_size) < self.y);
assert!(self.z < grid_size && -(grid_size) < self.z);
let x = (self.x + (grid_size) / 2) as usize;
let y = (self.y + (grid_size) / 2) as usize;
let z = (self.z + (grid_size) / 2) as usize;
let linear_index =
(grid_size as usize * grid_size as usize) * z
+ (grid_size as usize) * y
+ x;
if linear_index >= (grid_size * grid_size * grid_size) as usize {
eprintln!("AHHH SOMETHING WENT WRONG {:?} gives {}", self, linear_index);
}
return linear_index;
}
}

View File

@ -0,0 +1,23 @@
use crate::system::{GriddedPosition, Storage};
pub struct VectorStorage {
backing: Vec<bool>,
grid_size: u32,
dimension: u32,
}
impl VectorStorage {
pub fn new(grid_size: u32, dimension: u32) -> VectorStorage {
VectorStorage { grid_size, dimension, backing: vec![false; grid_size.pow(dimension) as usize] }
}
}
impl<P: GriddedPosition> Storage<P> for VectorStorage {
fn is_occupied(&self, position: &P) -> bool {
return self.backing[position.linear_index(self.grid_size)];
}
fn deposit(&mut self, position: &P) {
self.backing[position.linear_index(self.grid_size)] = true;
}
}

51
src/system/spawner.rs Normal file
View File

@ -0,0 +1,51 @@
use std::f32::consts::PI;
use rand::Rng;
use crate::system::Position;
use crate::system::spaces::continuous::P3;
use crate::system::spaces::hexagonal::HexPosition;
use crate::system::spaces::square_grid::{Grid2D, Grid3D};
pub trait Spawner<P: Position> {
fn spawn<R: Rng>(&self, rng: &mut R, radius: f32) -> P;
}
pub struct UniformSpawner;
impl Spawner<Grid2D> for UniformSpawner {
fn spawn<R: Rng>(&self, rng: &mut R, radius: f32) -> Grid2D {
let theta = rng.gen_range(0f32..1.0) * 2.0 * PI;
let (x, y) = (radius * theta.cos(), radius * theta.sin());
Grid2D::from_cartesian([x, y])
}
}
impl Spawner<HexPosition> for UniformSpawner {
fn spawn<R: Rng>(&self, rng: &mut R, radius: f32) -> HexPosition {
let theta = rng.gen_range(0f32..1.0) * 2.0 * PI;
let (x, y) = (radius * theta.cos(), radius * theta.sin());
HexPosition::from_cartesian([x, y])
}
}
impl Spawner<Grid3D> for UniformSpawner {
fn spawn<R: Rng>(&self, rng: &mut R, radius: f32) -> Grid3D {
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()
);
Grid3D::from_cartesian([x, y, z])
}
}
impl Spawner<P3> for UniformSpawner {
fn spawn<R: Rng>(&self, rng: &mut R, radius: f32) -> P3 {
P3::random_with_radius(rng, radius)
}
}

29
src/system/sticker.rs Normal file
View File

@ -0,0 +1,29 @@
use rand::Rng;
use crate::system::{GriddedPosition, Position, Storage};
pub trait Sticker<P: Position, S: Storage<P>> {
fn should_stick<R: Rng>(&self, rng: &mut R, space: &S, position: &P) -> bool;
}
pub struct SimpleSticking;
pub struct ProbabilisticSticking {
pub stick_probability: f32
}
impl<P: GriddedPosition, S: Storage<P>> Sticker<P, S> for SimpleSticking {
fn should_stick<R: Rng>(&self, _rng: &mut R, space: &S, position: &P) -> bool {
(0..P::NEIGHBOURS)
.map(|n| position.neighbour(n))
.any(|neighbour| space.is_occupied(&neighbour))
}
}
impl<P: GriddedPosition, S: Storage<P>> Sticker<P, S> for ProbabilisticSticking {
fn should_stick<R: Rng>(&self, rng: &mut R, space: &S, position: &P) -> bool {
(0..P::NEIGHBOURS)
.map(|n| position.neighbour(n))
.any(|neighbour| space.is_occupied(&neighbour) && rng.gen_range(0.0f32..=1.0) < self.stick_probability)
}
}

View File

@ -1,31 +1,32 @@
use rand::prelude::Rng;
use crate::system::GriddedPosition;
use crate::system::{GriddedPosition, Position};
pub trait Walker<P: GriddedPosition> {
pub trait Walker<P: Position> {
fn walk<R: Rng>(&self, rng: &mut R, position: &P) -> P;
}
pub struct LocalRandomWalker;
impl<Position: GriddedPosition> Walker<Position> for LocalRandomWalker {
fn walk<R: Rng>(&self, rng: &mut R, position: &Position) -> Position {
position.neighbour(rng.gen_range(0u32..Position::NEIGHBOURS))
impl<P: GriddedPosition> Walker<P> for LocalRandomWalker {
fn walk<R: Rng>(&self, rng: &mut R, position: &P) -> P {
position.neighbour(rng.gen_range(0u32..P::NEIGHBOURS))
}
}
mod test {
use rand::rngs::SmallRng;
use rand::{SeedableRng, thread_rng};
use crate::system::{GriddedPosition, grid::Position};
use crate::system::{GriddedPosition, Position};
use crate::system::spaces::square_grid::Grid2D;
use crate::system::walker::{LocalRandomWalker, Walker};
#[test]
fn uniformity() {
let walker = LocalRandomWalker;
let mut rng = SmallRng::from_rng(thread_rng()).unwrap();
let mut results: Vec<Position> = vec![];
let mut results: Vec<Grid2D> = vec![];
let origin = &Position::zero();
let origin = &Grid2D::zero();
let x: u32 = (1_000_000);
for i in 0..x {
@ -34,22 +35,22 @@ mod test {
let a = results
.iter()
.filter(|a| **a == Position { x: 0, y: 1 })
.filter(|a| **a == Grid2D { x: 0, y: 1 })
.count();
let b = results
.iter()
.filter(|a| **a == Position { x: 0, y: -1 })
.filter(|a| **a == Grid2D { x: 0, y: -1 })
.count();
let c = results
.iter()
.filter(|a| **a == Position { x: 1, y: 0 })
.filter(|a| **a == Grid2D { x: 1, y: 0 })
.count();
let d = results
.iter()
.filter(|a| **a == Position { x: -1, y: 0 })
.filter(|a| **a == Grid2D { x: -1, y: 0 })
.count();
println!("{} {} {} {}", a as f32 / x as f32, b as f32 / x as f32, c as f32 / x as f32, d as f32 / x as f32);