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//! Time Series Forecast (TSF).
use std::collections::VecDeque;
use crate::error::{Error, Result};
use crate::traits::Indicator;
/// Time Series Forecast (`TSF`): the rolling least-squares line projected one bar
/// past the window.
///
/// Over the last `period` inputs, indexed `x = 0, 1, …, period − 1`, it fits
/// `y = a + b·x` by ordinary least squares and reports the line's value at
/// `x = period` (one step beyond the most recent point):
///
/// ```text
/// b (slope) = (n·Σxy − Σx·Σy) / (n·Σxx − (Σx)²)
/// a (intercept) = (Σy − b·Σx) / n
/// TSF = a + b·period
/// ```
///
/// Where [`LinearRegression`](crate::LinearRegression) evaluates the fit at the
/// current bar (`a + b·(period − 1)`), `TSF` advances it one further bar, giving a
/// trend-following one-step-ahead forecast. Each update is O(1).
///
/// # Example
///
/// ```
/// use wickra_core::{Indicator, Tsf};
///
/// let mut indicator = Tsf::new(14).unwrap();
/// let mut last = None;
/// for i in 0..80 {
/// last = indicator.update(f64::from(i));
/// }
/// assert!(last.is_some());
/// ```
#[derive(Debug, Clone)]
pub struct Tsf {
period: usize,
window: VecDeque<f64>,
sum_x: f64,
denom: f64,
sum_y: f64,
sum_xy: f64,
}
impl Tsf {
/// Construct a new rolling time-series forecast over `period` inputs.
///
/// # Errors
/// Returns [`Error::InvalidPeriod`] if `period < 2` — a regression line is
/// undefined for fewer than two points.
pub fn new(period: usize) -> Result<Self> {
if period < 2 {
return Err(Error::InvalidPeriod {
message: "time series forecast needs period >= 2",
});
}
let n = period as f64;
let sum_x = n * (n - 1.0) / 2.0;
let sum_xx = (n - 1.0) * n * (2.0 * n - 1.0) / 6.0;
Ok(Self {
period,
window: VecDeque::with_capacity(period),
sum_x,
denom: n * sum_xx - sum_x * sum_x,
sum_y: 0.0,
sum_xy: 0.0,
})
}
/// Configured period.
pub const fn period(&self) -> usize {
self.period
}
}
impl Indicator for Tsf {
type Input = f64;
type Output = f64;
fn update(&mut self, value: f64) -> Option<f64> {
if self.window.len() == self.period {
let y0 = self.window.pop_front().expect("non-empty");
self.sum_xy = self.sum_xy - self.sum_y + y0;
self.sum_y -= y0;
}
let k = self.window.len() as f64;
self.window.push_back(value);
self.sum_y += value;
self.sum_xy += k * value;
if self.window.len() < self.period {
return None;
}
let n = self.period as f64;
let slope = (n * self.sum_xy - self.sum_x * self.sum_y) / self.denom;
let intercept = (self.sum_y - slope * self.sum_x) / n;
Some(intercept + slope * n)
}
fn reset(&mut self) {
self.window.clear();
self.sum_y = 0.0;
self.sum_xy = 0.0;
}
fn warmup_period(&self) -> usize {
self.period
}
fn is_ready(&self) -> bool {
self.window.len() == self.period
}
fn name(&self) -> &'static str {
"TSF"
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::traits::BatchExt;
use approx::assert_relative_eq;
#[test]
fn rejects_short_period() {
assert!(matches!(Tsf::new(1), Err(Error::InvalidPeriod { .. })));
}
#[test]
fn accessors_report_config() {
let tsf = Tsf::new(5).unwrap();
assert_eq!(tsf.period(), 5);
assert_eq!(tsf.name(), "TSF");
assert_eq!(tsf.warmup_period(), 5);
assert!(!tsf.is_ready());
}
#[test]
fn reference_value() {
// period 3 over [1, 2, 9]: fit y = 0 + 4x, forecast at x = 3 is 12.
let mut tsf = Tsf::new(3).unwrap();
let out: Vec<Option<f64>> = tsf.batch(&[1.0, 2.0, 9.0]);
assert!(out[0].is_none());
assert!(out[1].is_none());
assert_relative_eq!(out[2].unwrap(), 12.0, epsilon = 1e-9);
assert!(tsf.is_ready());
}
#[test]
fn forecasts_a_clean_line_one_step_ahead() {
// Window [10, 12, 14]: y = 10 + 2x, forecast at x = 3 is 16.
let mut tsf = Tsf::new(3).unwrap();
let out: Vec<Option<f64>> = tsf.batch(&[1.0, 10.0, 12.0, 14.0]);
assert_relative_eq!(out[3].unwrap(), 16.0, epsilon = 1e-9);
}
#[test]
fn reset_clears_state() {
let mut tsf = Tsf::new(3).unwrap();
let _ = tsf.batch(&[1.0, 2.0, 9.0]);
assert!(tsf.is_ready());
tsf.reset();
assert!(!tsf.is_ready());
assert_eq!(tsf.update(1.0), None);
}
}