Adds the reset tests the audit named as missing (aroon, awesome oscillator, donchian, keltner, williams_r, and both VWAP variants), non-finite-input tests for every scalar indicator that guards is_finite (WMA, RSI, MACD, Bollinger, KAMA), and naive-reference proptests for EMA, RSI and ATR. 189 core tests pass.
236 lines
6.3 KiB
Rust
236 lines
6.3 KiB
Rust
//! Volume-Weighted Average Price (VWAP).
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//!
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//! Two variants are offered: a cumulative `Vwap` that runs forever (the
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//! intraday convention), and a rolling-window `RollingVwap` for streaming bots
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//! that need a finite-memory price benchmark.
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use std::collections::VecDeque;
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use crate::error::{Error, Result};
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use crate::ohlcv::Candle;
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use crate::traits::Indicator;
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/// Cumulative session VWAP. Call [`Indicator::reset`] at the start of each
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/// session (e.g. trading-day boundary) to restart the accumulation.
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#[derive(Debug, Clone, Default)]
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pub struct Vwap {
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sum_pv: f64,
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sum_v: f64,
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has_emitted: bool,
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}
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impl Vwap {
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/// Construct a fresh cumulative VWAP.
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pub const fn new() -> Self {
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Self {
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sum_pv: 0.0,
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sum_v: 0.0,
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has_emitted: false,
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}
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}
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/// Current VWAP if at least one candle with non-zero volume has been observed.
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pub fn value(&self) -> Option<f64> {
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if self.sum_v == 0.0 {
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None
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} else {
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Some(self.sum_pv / self.sum_v)
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}
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}
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}
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impl Indicator for Vwap {
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type Input = Candle;
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type Output = f64;
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fn update(&mut self, candle: Candle) -> Option<f64> {
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let tp = candle.typical_price();
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self.sum_pv += tp * candle.volume;
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self.sum_v += candle.volume;
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if self.sum_v == 0.0 {
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return None;
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}
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self.has_emitted = true;
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Some(self.sum_pv / self.sum_v)
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}
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fn reset(&mut self) {
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self.sum_pv = 0.0;
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self.sum_v = 0.0;
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self.has_emitted = false;
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}
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fn warmup_period(&self) -> usize {
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1
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}
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fn is_ready(&self) -> bool {
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self.has_emitted
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}
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fn name(&self) -> &'static str {
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"VWAP"
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}
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}
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/// Rolling-window VWAP: a finite-memory variant for bots that don't want
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/// unbounded accumulation.
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#[derive(Debug, Clone)]
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pub struct RollingVwap {
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period: usize,
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window: VecDeque<(f64, f64)>, // (typical_price * volume, volume)
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sum_pv: f64,
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sum_v: f64,
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}
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impl RollingVwap {
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/// # Errors
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/// Returns [`Error::PeriodZero`] if `period == 0`.
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pub fn new(period: usize) -> Result<Self> {
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if period == 0 {
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return Err(Error::PeriodZero);
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}
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Ok(Self {
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period,
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window: VecDeque::with_capacity(period),
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sum_pv: 0.0,
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sum_v: 0.0,
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})
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}
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/// Configured rolling window length.
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pub const fn period(&self) -> usize {
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self.period
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}
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}
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impl Indicator for RollingVwap {
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type Input = Candle;
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type Output = f64;
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fn update(&mut self, candle: Candle) -> Option<f64> {
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let pv = candle.typical_price() * candle.volume;
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if self.window.len() == self.period {
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let (old_pv, old_v) = self.window.pop_front().expect("non-empty");
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self.sum_pv -= old_pv;
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self.sum_v -= old_v;
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}
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self.window.push_back((pv, candle.volume));
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self.sum_pv += pv;
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self.sum_v += candle.volume;
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if self.window.len() < self.period || self.sum_v == 0.0 {
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return None;
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}
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Some(self.sum_pv / self.sum_v)
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}
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fn reset(&mut self) {
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self.window.clear();
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self.sum_pv = 0.0;
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self.sum_v = 0.0;
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}
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fn warmup_period(&self) -> usize {
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self.period
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}
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fn is_ready(&self) -> bool {
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self.window.len() == self.period && self.sum_v > 0.0
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}
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fn name(&self) -> &'static str {
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"RollingVWAP"
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}
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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use crate::traits::BatchExt;
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use approx::assert_relative_eq;
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fn c(price: f64, volume: f64) -> Candle {
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Candle::new(price, price, price, price, volume, 0).unwrap()
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}
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#[test]
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fn cumulative_vwap_equal_volumes_equals_mean() {
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let candles = vec![c(10.0, 1.0), c(20.0, 1.0), c(30.0, 1.0)];
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let mut v = Vwap::new();
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let out = v.batch(&candles);
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assert_relative_eq!(out[2].unwrap(), 20.0, epsilon = 1e-12);
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}
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#[test]
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fn cumulative_vwap_weighted() {
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// Two candles: 10@1 and 20@3 -> (10*1 + 20*3) / (1+3) = 70/4 = 17.5
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let candles = vec![c(10.0, 1.0), c(20.0, 3.0)];
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let mut v = Vwap::new();
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let out = v.batch(&candles);
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assert_relative_eq!(out[1].unwrap(), 17.5, epsilon = 1e-12);
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}
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#[test]
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fn rolling_vwap_window_slides() {
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let candles = vec![c(10.0, 1.0), c(20.0, 1.0), c(30.0, 1.0), c(40.0, 1.0)];
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let mut v = RollingVwap::new(3).unwrap();
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let out = v.batch(&candles);
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assert!(out[1].is_none());
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// index 2 -> (10+20+30)/3 = 20
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assert_relative_eq!(out[2].unwrap(), 20.0, epsilon = 1e-12);
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// index 3 -> (20+30+40)/3 = 30
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assert_relative_eq!(out[3].unwrap(), 30.0, epsilon = 1e-12);
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}
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#[test]
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fn batch_equals_streaming_cumulative() {
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let candles: Vec<Candle> = (1..20).map(|i| c(f64::from(i), 1.0)).collect();
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let mut a = Vwap::new();
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let mut b = Vwap::new();
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assert_eq!(
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a.batch(&candles),
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candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
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);
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}
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#[test]
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fn batch_equals_streaming_rolling() {
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let candles: Vec<Candle> = (1..30)
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.map(|i| c(f64::from(i), f64::from(i % 5 + 1)))
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.collect();
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let mut a = RollingVwap::new(10).unwrap();
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let mut b = RollingVwap::new(10).unwrap();
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assert_eq!(
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a.batch(&candles),
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candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
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);
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}
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#[test]
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fn rolling_rejects_zero_period() {
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assert!(RollingVwap::new(0).is_err());
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}
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#[test]
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fn cumulative_reset_clears_state() {
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let candles = vec![c(10.0, 1.0), c(20.0, 1.0), c(30.0, 1.0)];
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let mut v = Vwap::new();
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v.batch(&candles);
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assert!(v.is_ready());
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v.reset();
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assert!(!v.is_ready());
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assert_eq!(v.value(), None);
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}
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#[test]
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fn rolling_reset_clears_state() {
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let candles: Vec<Candle> = (1..=10).map(|i| c(f64::from(i), 1.0)).collect();
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let mut v = RollingVwap::new(5).unwrap();
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v.batch(&candles);
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assert!(v.is_ready());
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v.reset();
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assert!(!v.is_ready());
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assert_eq!(v.update(candles[0]), None);
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}
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}
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