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wickra/crates/wickra-core/src/indicators/tweezer.rs
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kingchencandGitHub 0479191b66 feat: signed candlestick directional ±1 encoding (Doji signed mode) (#111)
* feat(core): add signed dragonfly/gravestone encoding to Doji

Doji gains an opt-in `.signed()` mode that classifies a detected Doji by the
position of its body within the bar range: dragonfly (long lower shadow) emits
+1.0 (bullish), gravestone (long upper shadow) emits -1.0 (bearish), and a
long-legged/standard Doji emits 0.0. The default detection-flag behaviour
(+1.0/0.0) is unchanged, so existing callers are unaffected.

The other 14 candlestick patterns already emit the uniform +1 bull / -1 bear /
0 none convention; document that explicitly with a "Signed +-1 encoding"
section on each so the whole family is a consistent drop-in ML feature.

* feat(bindings): expose Doji signed mode in python, node, wasm

Hand-write the Doji binding in all three language bindings (instead of the
shared candle-pattern macro) so it accepts an opt-in `signed` flag and exposes
an `is_signed`/`isSigned` accessor:

- Python: `Doji(signed=False)` keyword argument
- Node: `new Doji(signed?)` optional constructor argument (index.d.ts/.js
  regenerated via napi build)
- WASM: `new Doji(signed?)` optional constructor argument

The default construction is unchanged, so existing callers keep the
direction-less +1/0 detection flag.

* test(bindings,fuzz): cover Doji signed dragonfly/gravestone encoding

- python: dragonfly(+1)/gravestone(-1)/neutral(0) and default-flag cases in
  test_known_values
- node: equivalent signed/default assertions in indicators.test.js
- fuzz: drive a signed Doji alongside the default in indicator_update_candle

* docs: document signed candlestick convention and Doji signed mode

README gains a candlestick sign-convention note; CHANGELOG records the new
opt-in Doji signed dragonfly/gravestone encoding under [Unreleased].
2026-06-01 14:37:20 +02:00

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//! Tweezer Top / Bottom candlestick pattern.
use crate::error::{Error, Result};
use crate::ohlcv::Candle;
use crate::traits::Indicator;
/// Tweezer — a 2-bar reversal pattern where two consecutive candles share an
/// extreme.
///
/// ```text
/// tol = tolerance * |prev.high| + tolerance * |prev.low| (per leg)
/// tweezer_top = |curr.high prev.high| <= tol_high
/// tweezer_bot = |curr.low prev.low| <= tol_low
/// ```
///
/// The output is `1.0` for a Tweezer Top (matched highs), `+1.0` for a
/// Tweezer Bottom (matched lows), and `0.0` otherwise. If *both* extremes
/// match — a flat pair of candles — the bottom wins by convention (bullish
/// rejection of the low). `tolerance` defaults to `0.001` (10 bps relative)
/// and must lie in `[0, 1)`.
///
/// Pattern-shape check only — no trend filter is applied; combine with a trend
/// indicator for actionable signals.
///
/// # Signed ±1 encoding
///
/// This detector already emits the uniform candlestick sign convention shared
/// across the pattern family — `+1.0` bullish, `1.0` bearish, `0.0` no
/// pattern — so it drops straight into a machine-learning feature matrix where
/// the bullish and bearish variants of the pattern occupy a single dimension.
///
/// # Example
///
/// ```
/// use wickra_core::{Candle, Indicator, Tweezer};
///
/// let mut indicator = Tweezer::new();
/// indicator.update(Candle::new(11.0, 12.0, 9.5, 9.6, 1.0, 0).unwrap());
/// // Matching low.
/// let out = indicator.update(Candle::new(9.7, 10.5, 9.5, 10.2, 1.0, 1).unwrap());
/// assert_eq!(out, Some(1.0));
/// ```
#[derive(Debug, Clone)]
pub struct Tweezer {
tolerance: f64,
prev: Option<Candle>,
has_emitted: bool,
}
impl Default for Tweezer {
fn default() -> Self {
Self::new()
}
}
impl Tweezer {
/// Construct a Tweezer detector with the default relative tolerance (1e-3).
pub const fn new() -> Self {
Self {
tolerance: 0.001,
prev: None,
has_emitted: false,
}
}
/// Construct a Tweezer detector with a custom relative tolerance.
///
/// `tolerance` must lie in `[0, 1)`.
pub fn with_tolerance(tolerance: f64) -> Result<Self> {
if !(0.0..1.0).contains(&tolerance) {
return Err(Error::InvalidPeriod {
message: "tweezer tolerance must lie in [0, 1)",
});
}
Ok(Self {
tolerance,
prev: None,
has_emitted: false,
})
}
/// Configured relative tolerance.
pub fn tolerance(&self) -> f64 {
self.tolerance
}
}
impl Indicator for Tweezer {
type Input = Candle;
type Output = f64;
fn update(&mut self, candle: Candle) -> Option<f64> {
self.has_emitted = true;
let prev = self.prev;
self.prev = Some(candle);
let Some(p) = prev else {
return Some(0.0);
};
let tol_high = self.tolerance * p.high.abs().max(candle.high.abs());
let tol_low = self.tolerance * p.low.abs().max(candle.low.abs());
let match_low = (candle.low - p.low).abs() <= tol_low;
let match_high = (candle.high - p.high).abs() <= tol_high;
if match_low {
Some(1.0)
} else if match_high {
Some(-1.0)
} else {
Some(0.0)
}
}
fn reset(&mut self) {
self.prev = None;
self.has_emitted = false;
}
fn warmup_period(&self) -> usize {
2
}
fn is_ready(&self) -> bool {
self.has_emitted
}
fn name(&self) -> &'static str {
"Tweezer"
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::traits::BatchExt;
fn c(open: f64, high: f64, low: f64, close: f64, ts: i64) -> Candle {
Candle::new(open, high, low, close, 1.0, ts).unwrap()
}
#[test]
fn rejects_invalid_tolerance() {
assert!(Tweezer::with_tolerance(-0.01).is_err());
assert!(Tweezer::with_tolerance(1.0).is_err());
}
#[test]
fn accepts_valid_tolerance() {
let t = Tweezer::with_tolerance(0.0).unwrap();
assert!((t.tolerance() - 0.0).abs() < 1e-12);
}
#[test]
fn accessors_and_metadata() {
let t = Tweezer::default();
assert_eq!(t.name(), "Tweezer");
assert_eq!(t.warmup_period(), 2);
assert!(!t.is_ready());
assert!((t.tolerance() - 0.001).abs() < 1e-12);
}
#[test]
fn tweezer_bottom_is_plus_one() {
let mut t = Tweezer::new();
assert_eq!(t.update(c(11.0, 12.0, 9.5, 9.6, 0)), Some(0.0));
// Matching low 9.5.
assert_eq!(t.update(c(9.7, 10.5, 9.5, 10.2, 1)), Some(1.0));
}
#[test]
fn tweezer_top_is_minus_one() {
let mut t = Tweezer::new();
assert_eq!(t.update(c(9.0, 12.0, 8.5, 11.0, 0)), Some(0.0));
// Matching high 12.0.
assert_eq!(t.update(c(11.5, 12.0, 11.0, 11.4, 1)), Some(-1.0));
}
#[test]
fn distinct_extremes_yield_zero() {
let mut t = Tweezer::new();
t.update(c(10.0, 11.0, 9.0, 10.5, 0));
assert_eq!(t.update(c(10.6, 11.5, 9.6, 11.2, 1)), Some(0.0));
}
#[test]
fn first_bar_returns_zero() {
let mut t = Tweezer::new();
assert_eq!(t.update(c(10.0, 11.0, 9.0, 10.5, 0)), Some(0.0));
}
#[test]
fn matched_both_extremes_prefers_bottom() {
// Identical candles match both highs and lows -> bottom (+1.0).
let mut t = Tweezer::new();
t.update(c(10.0, 11.0, 9.0, 10.5, 0));
assert_eq!(t.update(c(10.0, 11.0, 9.0, 10.5, 1)), Some(1.0));
}
#[test]
fn batch_equals_streaming() {
let candles: Vec<Candle> = (0..40)
.map(|i| {
let base = 100.0 + (i as f64 * 0.1).sin();
c(base, base + 2.0, base - 2.0, base + 0.5, i)
})
.collect();
let mut a = Tweezer::new();
let mut b = Tweezer::new();
assert_eq!(
a.batch(&candles),
candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
);
}
#[test]
fn reset_clears_state() {
let mut t = Tweezer::new();
t.update(c(10.0, 11.0, 9.0, 10.5, 0));
t.update(c(10.0, 11.0, 9.0, 10.5, 1));
assert!(t.is_ready());
t.reset();
assert!(!t.is_ready());
assert_eq!(t.update(c(10.0, 11.0, 9.0, 10.5, 0)), Some(0.0));
}
}