use serde::{Deserialize, Serialize};
#[typetag::serde]
pub trait Evaluator: std::fmt::Debug + Sync + Send {
fn evaluate(&self, value: f32) -> f32;
}
#[derive(Debug, Serialize, Deserialize)]
pub struct LinearEvaluator {
xa: f32,
ya: f32,
dy_over_dx: f32,
}
impl LinearEvaluator {
pub fn new(xa: f32, ya: f32, xb: f32, yb: f32) -> Self {
Self {
xa,
ya,
dy_over_dx: (yb - ya) / (xb - xa),
}
}
}
impl Default for LinearEvaluator {
fn default() -> Self {
Self::new(0.0, 0.0, 100.0, 100.0)
}
}
#[typetag::serde]
impl Evaluator for LinearEvaluator {
fn evaluate(&self, value: f32) -> f32 {
clamp(self.ya + self.dy_over_dx * (value - self.xa), 0.0, 1.0)
}
}
#[derive(Debug, Serialize, Deserialize)]
pub struct PowerEvaluator {
xa: f32,
ya: f32,
xb: f32,
power: f32,
dy: f32,
}
impl PowerEvaluator {
pub fn new(power: f32, xa: f32, ya: f32, xb: f32, yb: f32) -> Self {
Self {
power: clamp(power, 0.0, 10000.0),
dy: yb - ya,
xa,
ya,
xb,
}
}
}
impl Default for PowerEvaluator {
fn default() -> Self {
Self::new(2.0, 0.0, 0.0, 100.0, 100.0)
}
}
#[typetag::serde]
impl Evaluator for PowerEvaluator {
fn evaluate(&self, value: f32) -> f32 {
let cx = clamp(value, self.xa, self.xb);
self.dy * ((cx - self.xa) / (self.xb - self.xa)).powf(self.power) + self.ya
}
}
#[derive(Debug, Serialize, Deserialize)]
pub struct SigmoidEvaluator {
xa: f32,
xb: f32,
k: f32,
two_over_dx: f32,
x_mean: f32,
y_mean: f32,
dy_over_two: f32,
one_minus_k: f32,
}
impl SigmoidEvaluator {
pub fn new(k: f32, xa: f32, ya: f32, xb: f32, yb: f32) -> Self {
let k = clamp(k, -0.99999, 0.99999);
Self {
xa,
xb,
two_over_dx: (2.0 / (xb - ya)).abs(),
x_mean: (xa + xb) / 2.0,
y_mean: (ya + yb) / 2.0,
dy_over_two: (yb - ya) / 2.0,
one_minus_k: 1.0 - k,
k,
}
}
}
#[typetag::serde]
impl Evaluator for SigmoidEvaluator {
fn evaluate(&self, x: f32) -> f32 {
let cx_minus_x_mean = clamp(x, self.xa, self.xb) - self.x_mean;
let numerator = self.two_over_dx * cx_minus_x_mean * self.one_minus_k;
let denominator = self.k * (1.0 - 2.0 * (self.two_over_dx * cx_minus_x_mean)).abs() + 1.0;
self.dy_over_two * (numerator / denominator) + self.y_mean
}
}
impl Default for SigmoidEvaluator {
fn default() -> Self {
Self::new(-0.5, 0.0, 0.0, 100.0, 100.0)
}
}
fn clamp<T: PartialOrd>(val: T, min: T, max: T) -> T {
let val = if val > max { max } else { val };
if val < min {
min
} else {
val
}
}