//! 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, 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 { 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 { 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> = 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> = 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); } }