logaritmisk/trueskill-rs
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Use f64 instead.

Browse Source
This commit is contained in:
Anders Olsson
2018-10-23 14:59:58 +02:00
parent 1b840e737d
commit b4cce71df4
5 changed files with 38 additions and 38 deletions
Download Patch File Download Diff File Expand all files Collapse all files

22
src/factor_graph.rs
View File

@@ -113,7 +113,7 @@ pub struct LikelihoodFactor {
id: usize,
mean: VariableId,
value: VariableId,
variance: f32,
variance: f64,
}
impl LikelihoodFactor {
@@ -122,7 +122,7 @@ impl LikelihoodFactor {
id: usize,
mean: VariableId,
value: VariableId,
variance: f32,
variance: f64,
) -> LikelihoodFactor {
if let Some(variable) = variable_arena.get_mut(mean) {
variable.attach_factor(id);
@@ -183,7 +183,7 @@ pub struct SumFactor {
id: usize,
sum: VariableId,
terms: Vec<VariableId>,
coeffs: Vec<f32>,
coeffs: Vec<f64>,
}
impl SumFactor {
@@ -192,7 +192,7 @@ impl SumFactor {
id: usize,
sum: VariableId,
terms: Vec<VariableId>,
coeffs: Vec<f32>,
coeffs: Vec<f64>,
) -> SumFactor {
if let Some(variable) = variable_arena.get_mut(sum) {
variable.attach_factor(id);
@@ -218,7 +218,7 @@ impl SumFactor {
variable: VariableId,
y: Vec<Gaussian>,
fy: Vec<Gaussian>,
a: &Vec<f32>,
a: &Vec<f64>,
) {
let size = a.len();
@@ -313,21 +313,21 @@ impl SumFactor {
}
}
fn v_win(t: f32, e: f32) -> f32 {
fn v_win(t: f64, e: f64) -> f64 {
math::pdf(t - e) / math::cdf(t - e)
}
fn w_win(t: f32, e: f32) -> f32 {
fn w_win(t: f64, e: f64) -> f64 {
let vwin = v_win(t, e);
vwin * (vwin + t - e)
}
fn v_draw(t: f32, e: f32) -> f32 {
fn v_draw(t: f64, e: f64) -> f64 {
(math::pdf(-e - t) - math::pdf(e - t)) / (math::cdf(e - t) - math::cdf(-e - t))
}
fn w_draw(t: f32, e: f32) -> f32 {
fn w_draw(t: f64, e: f64) -> f64 {
let vdraw = v_draw(t, e);
let n = (vdraw * vdraw) + ((e - t) * math::pdf(e - t) + (e + t) * math::pdf(e + t));
let d = math::cdf(e - t) - math::cdf(-e - t);
@@ -338,7 +338,7 @@ fn w_draw(t: f32, e: f32) -> f32 {
pub struct TruncateFactor {
id: usize,
variable: VariableId,
epsilon: f32,
epsilon: f64,
draw: bool,
}
@@ -347,7 +347,7 @@ impl TruncateFactor {
variable_arena: &mut VariableArena,
id: usize,
variable: VariableId,
epsilon: f32,
epsilon: f64,
draw: bool,
) -> TruncateFactor {
if let Some(variable) = variable_arena.get_mut(variable) {

12
src/gaussian.rs
View File

@@ -2,8 +2,8 @@ use std::ops;
#[derive(Clone, Copy)]
pub struct Gaussian {
pub pi: f32,
pub tau: f32,
pub pi: f64,
pub tau: f64,
}
impl Gaussian {
@@ -11,17 +11,17 @@ impl Gaussian {
Gaussian::with_pi_tau(0.0, 0.0)
}
pub fn with_pi_tau(pi: f32, tau: f32) -> Gaussian {
pub fn with_pi_tau(pi: f64, tau: f64) -> Gaussian {
Gaussian { pi, tau }
}
pub fn with_mu_sigma(mu: f32, sigma: f32) -> Gaussian {
pub fn with_mu_sigma(mu: f64, sigma: f64) -> Gaussian {
let pi = 1.0 / sigma.powi(2);
Gaussian::with_pi_tau(pi, pi * mu)
}
pub fn mu(&self) -> f32 {
pub fn mu(&self) -> f64 {
if self.pi == 0.0 {
0.0
} else {
@@ -29,7 +29,7 @@ impl Gaussian {
}
}
pub fn sigma(&self) -> f32 {
pub fn sigma(&self) -> f64 {
(1.0 / self.pi).sqrt()
}
}

18
src/lib.rs
View File

@@ -8,27 +8,27 @@ use gaussian::Gaussian;
use matrix::Matrix;
/// Default initial mean of ratings.
const MU: f32 = 25.0;
const MU: f64 = 25.0;
/// Default initial standard deviation of ratings.
const SIGMA: f32 = MU / 3.0;
const SIGMA: f64 = MU / 3.0;
/// Default distance that guarantees about 76% chance of winning.
const BETA: f32 = SIGMA / 2.0;
const BETA: f64 = SIGMA / 2.0;
/// Default dynamic factor.
const TAU: f32 = SIGMA / 100.0;
const TAU: f64 = SIGMA / 100.0;
/// Default draw probability of the game.
const DRAW_PROBABILITY: f32 = 0.10;
const DRAW_PROBABILITY: f64 = 0.10;
/// A basis to check reliability of the result.
const DELTA: f32 = 0.0001;
const DELTA: f64 = 0.0001;
#[derive(Debug, PartialEq)]
pub struct Rating {
pub mu: f32,
pub sigma: f32,
pub mu: f64,
pub sigma: f64,
}
impl Default for Rating {
@@ -191,7 +191,7 @@ fn rate(rating_groups: &[&[Rating]]) {
}
}
fn quality(rating_groups: &[&[Rating]]) -> f32 {
fn quality(rating_groups: &[&[Rating]]) -> f64 {
let flatten_ratings = rating_groups
.iter()
.flat_map(|group| group.iter())

12
src/math.rs
View File

@@ -1,6 +1,6 @@
use std::f32;
use std::f64;
fn erfc(x: f32) -> f32 {
fn erfc(x: f64) -> f64 {
let z = x.abs();
let t = 1.0 / (1.0 + z / 2.0);
let r = t
@@ -21,10 +21,10 @@ fn erfc(x: f32) -> f32 {
}
}
pub fn cdf(x: f32) -> f32 {
0.5 * erfc(-x / 2.0f32.sqrt())
pub fn cdf(x: f64) -> f64 {
0.5 * erfc(-x / 2.0f64.sqrt())
}
pub fn pdf(x: f32) -> f32 {
1.0 / (2.0 * f32::consts::PI).sqrt() * (-((x / 1.0).powi(2) / 2.0)).exp()
pub fn pdf(x: f64) -> f64 {
1.0 / (2.0 * f64::consts::PI).sqrt() * (-((x / 1.0).powi(2) / 2.0)).exp()
}

12
src/matrix.rs
View File

@@ -1,6 +1,6 @@
use std::ops;
fn det(m: &[f32], x: usize) -> f32 {
fn det(m: &[f64], x: usize) -> f64 {
if x == 1 {
m[0]
} else if x == 2 {
@@ -17,7 +17,7 @@ fn det(m: &[f32], x: usize) -> f32 {
.map(|(_, v)| *v)
.collect::<Vec<_>>();
d += (-1.0f32).powi(n as i32) * m[n] * det(&ms, x - 1);
d += (-1.0f64).powi(n as i32) * m[n] * det(&ms, x - 1);
}
d
@@ -26,7 +26,7 @@ fn det(m: &[f32], x: usize) -> f32 {
#[derive(Clone, Debug)]
pub struct Matrix {
data: Box<[f32]>,
data: Box<[f64]>,
height: usize,
width: usize,
}
@@ -80,7 +80,7 @@ impl Matrix {
matrix
}
pub fn determinant(&self) -> f32 {
pub fn determinant(&self) -> f64 {
debug_assert!(self.width == self.height);
det(&self.data, self.width)
@@ -122,7 +122,7 @@ impl Matrix {
}
impl ops::Index<(usize, usize)> for Matrix {
type Output = f32;
type Output = f64;
fn index(&self, pos: (usize, usize)) -> &Self::Output {
&self.data[(self.width * pos.0) + pos.1]
@@ -135,7 +135,7 @@ impl ops::IndexMut<(usize, usize)> for Matrix {
}
}
impl<'a> ops::Mul<&'a Matrix> for f32 {
impl<'a> ops::Mul<&'a Matrix> for f64 {
type Output = Matrix;
fn mul(self, rhs: &'a Matrix) -> Matrix {