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F13b: add True Range, Chaikin Volatility, Z-Score and Linear Regression Angle

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Second half of the eight indicators that fill out the new family taxonomy.

- Rust core: true_range.rs (TrueRange — the raw single-bar volatility ATR
  averages), chaikin_volatility.rs (ChaikinVolatility — rate of change of a
  smoothed high-low spread), z_score.rs (ZScore — price normalised against
  its rolling mean and standard deviation) and linreg_angle.rs (LinRegAngle
  — the rolling regression slope as a degree angle). Each with a full
  Indicator impl, runnable doctest and reference / property / warmup /
  reset / batch==streaming tests.
- Python / Node / WASM: classes wired through all three bindings (ZScore
  and LinRegAngle ride the scalar macros where possible) plus .pyi stubs
  and __init__.py / __all__ entries.
- Wiki: four new Indicator-*.md pages.

The eight-family taxonomy restructure (Overview / Home / README / folder
layout) lands next in F13c.

cargo fmt + clippy (core/wickra/data/wasm/node) clean; 508 core tests,
25 data tests and 74 doctests green.
This commit is contained in:
kingchenc
2026-05-22 21:06:36 +02:00
parent e452d35a27
commit 6643f7a81d
16 changed files with 1837 additions and 7 deletions
Download Patch File Download Diff File Expand all files Collapse all files
bindings/node/index.js
+5 -1
View File
@@ -310,7 +310,7 @@ if (!nativeBinding) {
throw new Error(`Failed to load native binding`)
}
const { version, SMA, EMA, WMA, RSI, DEMA, TEMA, HMA, ROC, TRIX, SMMA, TRIMA, ZLEMA, MOM, CMO, DPO, StdDev, UlcerIndex, VerticalHorizontalFilter, MACD, BollingerBands, ATR, Stochastic, OBV, ADX, CCI, WilliamsR, MFI, PSAR, Keltner, Donchian, VWAP, AwesomeOscillator, Aroon, KAMA, T3, TSI, PMO, ADL, VolumePriceTrend, ChaikinMoneyFlow, ChaikinOscillator, ForceIndex, EaseOfMovement, SuperTrend, ChandelierExit, ChandeKrollStop, AtrTrailingStop, TypicalPrice, MedianPrice, WeightedClose, LinearRegression, LinRegSlope, AcceleratorOscillator, BalanceOfPower, ChoppinessIndex, BollingerBandwidth, PercentB, NATR, HistoricalVolatility, AroonOscillator, Vortex, MassIndex, StochRSI, UltimateOscillator, PPO, Coppock, VWMA } = nativeBinding
const { version, SMA, EMA, WMA, RSI, DEMA, TEMA, HMA, ROC, TRIX, SMMA, TRIMA, ZLEMA, MOM, CMO, DPO, StdDev, UlcerIndex, VerticalHorizontalFilter, ZScore, MACD, BollingerBands, ATR, Stochastic, OBV, ADX, CCI, WilliamsR, MFI, PSAR, Keltner, Donchian, VWAP, AwesomeOscillator, Aroon, KAMA, T3, TSI, PMO, ADL, VolumePriceTrend, ChaikinMoneyFlow, ChaikinOscillator, ForceIndex, EaseOfMovement, SuperTrend, ChandelierExit, ChandeKrollStop, AtrTrailingStop, TypicalPrice, MedianPrice, WeightedClose, LinearRegression, LinRegSlope, AcceleratorOscillator, BalanceOfPower, ChoppinessIndex, TrueRange, ChaikinVolatility, LinRegAngle, BollingerBandwidth, PercentB, NATR, HistoricalVolatility, AroonOscillator, Vortex, MassIndex, StochRSI, UltimateOscillator, PPO, Coppock, VWMA } = nativeBinding
module.exports.version = version
module.exports.SMA = SMA
@@ -331,6 +331,7 @@ module.exports.DPO = DPO
module.exports.StdDev = StdDev
module.exports.UlcerIndex = UlcerIndex
module.exports.VerticalHorizontalFilter = VerticalHorizontalFilter
module.exports.ZScore = ZScore
module.exports.MACD = MACD
module.exports.BollingerBands = BollingerBands
module.exports.ATR = ATR
@@ -368,6 +369,9 @@ module.exports.LinRegSlope = LinRegSlope
module.exports.AcceleratorOscillator = AcceleratorOscillator
module.exports.BalanceOfPower = BalanceOfPower
module.exports.ChoppinessIndex = ChoppinessIndex
module.exports.TrueRange = TrueRange
module.exports.ChaikinVolatility = ChaikinVolatility
module.exports.LinRegAngle = LinRegAngle
module.exports.BollingerBandwidth = BollingerBandwidth
module.exports.PercentB = PercentB
module.exports.NATR = NATR
bindings/node/src/lib.rs
+150
View File
@@ -115,6 +115,7 @@ node_scalar_indicator!(
"VerticalHorizontalFilter",
wc::VerticalHorizontalFilter
);
node_scalar_indicator!(ZScoreNode, "ZScore", wc::ZScore);
// ============================== MACD ==============================
@@ -2216,6 +2217,155 @@ impl ChoppinessIndexNode {
}
}
// ============================== True Range ==============================
#[napi(js_name = "TrueRange")]
pub struct TrueRangeNode {
inner: wc::TrueRange,
}
impl Default for TrueRangeNode {
fn default() -> Self {
Self::new()
}
}
#[napi]
impl TrueRangeNode {
#[napi(constructor)]
pub fn new() -> Self {
Self {
inner: wc::TrueRange::new(),
}
}
#[napi]
pub fn update(&mut self, high: f64, low: f64, close: f64) -> napi::Result<Option<f64>> {
Ok(self.inner.update(cnd(high, low, close, 0.0)?))
}
#[napi]
pub fn batch(
&mut self,
high: Vec<f64>,
low: Vec<f64>,
close: Vec<f64>,
) -> napi::Result<Vec<f64>> {
if high.len() != low.len() || low.len() != close.len() {
return Err(NapiError::from_reason(
"high, low, close must be equal length".to_string(),
));
}
let mut out = Vec::with_capacity(high.len());
for i in 0..high.len() {
out.push(
self.inner
.update(cnd(high[i], low[i], close[i], 0.0)?)
.unwrap_or(f64::NAN),
);
}
Ok(out)
}
#[napi]
pub fn reset(&mut self) {
self.inner.reset();
}
#[napi(js_name = "isReady")]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[napi(js_name = "warmupPeriod")]
pub fn warmup_period(&self) -> u32 {
self.inner.warmup_period() as u32
}
}
// ============================== Chaikin Volatility ==============================
#[napi(js_name = "ChaikinVolatility")]
pub struct ChaikinVolatilityNode {
inner: wc::ChaikinVolatility,
}
#[napi]
impl ChaikinVolatilityNode {
#[napi(constructor)]
pub fn new(ema_period: u32, roc_period: u32) -> napi::Result<Self> {
Ok(Self {
inner: wc::ChaikinVolatility::new(ema_period as usize, roc_period as usize)
.map_err(map_err)?,
})
}
#[napi]
pub fn update(&mut self, high: f64, low: f64) -> napi::Result<Option<f64>> {
Ok(self.inner.update(cnd(high, low, low, 0.0)?))
}
#[napi]
pub fn batch(&mut self, high: Vec<f64>, low: Vec<f64>) -> napi::Result<Vec<f64>> {
if high.len() != low.len() {
return Err(NapiError::from_reason(
"high and low must be equal length".to_string(),
));
}
let mut out = Vec::with_capacity(high.len());
for i in 0..high.len() {
out.push(
self.inner
.update(cnd(high[i], low[i], low[i], 0.0)?)
.unwrap_or(f64::NAN),
);
}
Ok(out)
}
#[napi]
pub fn reset(&mut self) {
self.inner.reset();
}
#[napi(js_name = "isReady")]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[napi(js_name = "warmupPeriod")]
pub fn warmup_period(&self) -> u32 {
self.inner.warmup_period() as u32
}
}
// ============================== Linear Regression Angle ==============================
#[napi(js_name = "LinRegAngle")]
pub struct LinRegAngleNode {
inner: wc::LinRegAngle,
}
#[napi]
impl LinRegAngleNode {
#[napi(constructor)]
pub fn new(period: u32) -> napi::Result<Self> {
Ok(Self {
inner: wc::LinRegAngle::new(period as usize).map_err(map_err)?,
})
}
#[napi]
pub fn update(&mut self, value: f64) -> Option<f64> {
self.inner.update(value)
}
#[napi]
pub fn batch(&mut self, prices: Vec<f64>) -> Vec<f64> {
flatten(self.inner.batch(&prices))
}
#[napi]
pub fn reset(&mut self) {
self.inner.reset();
}
#[napi(js_name = "isReady")]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[napi(js_name = "warmupPeriod")]
pub fn warmup_period(&self) -> u32 {
self.inner.warmup_period() as u32
}
}
// ============================== Bollinger Bandwidth ==============================
#[napi(js_name = "BollingerBandwidth")]
bindings/python/python/wickra/__init__.py
+8
View File
@@ -82,6 +82,8 @@ from ._wickra import (
ChandelierExit,
ChandeKrollStop,
AtrTrailingStop,
TrueRange,
ChaikinVolatility,
# Volume
OBV,
VWAP,
@@ -97,6 +99,8 @@ from ._wickra import (
WeightedClose,
LinearRegression,
LinRegSlope,
ZScore,
LinRegAngle,
)
__all__ = [
@@ -158,6 +162,8 @@ __all__ = [
"ChandelierExit",
"ChandeKrollStop",
"AtrTrailingStop",
"TrueRange",
"ChaikinVolatility",
# Volume
"OBV",
"VWAP",
@@ -173,4 +179,6 @@ __all__ = [
"WeightedClose",
"LinearRegression",
"LinRegSlope",
"ZScore",
"LinRegAngle",
]
bindings/python/python/wickra/__init__.pyi
+47
View File
@@ -350,6 +350,53 @@ class VerticalHorizontalFilter:
@property
def period(self) -> int: ...
class TrueRange:
def __init__(self) -> None: ...
def update(self, candle: CandleLike) -> Optional[float]: ...
def batch(
self,
high: NDArray[np.float64],
low: NDArray[np.float64],
close: NDArray[np.float64],
) -> NDArray[np.float64]: ...
def reset(self) -> None: ...
def is_ready(self) -> bool: ...
def warmup_period(self) -> int: ...
class ChaikinVolatility:
def __init__(self, ema_period: int = 10, roc_period: int = 10) -> None: ...
def update(self, candle: CandleLike) -> Optional[float]: ...
def batch(
self,
high: NDArray[np.float64],
low: NDArray[np.float64],
) -> NDArray[np.float64]: ...
def reset(self) -> None: ...
def is_ready(self) -> bool: ...
def warmup_period(self) -> int: ...
@property
def periods(self) -> Tuple[int, int]: ...
class ZScore:
def __init__(self, period: int = 20) -> None: ...
def update(self, value: float) -> Optional[float]: ...
def batch(self, prices: NDArray[np.float64]) -> NDArray[np.float64]: ...
def reset(self) -> None: ...
def is_ready(self) -> bool: ...
def warmup_period(self) -> int: ...
@property
def period(self) -> int: ...
class LinRegAngle:
def __init__(self, period: int = 14) -> None: ...
def update(self, value: float) -> Optional[float]: ...
def batch(self, prices: NDArray[np.float64]) -> NDArray[np.float64]: ...
def reset(self) -> None: ...
def is_ready(self) -> bool: ...
def warmup_period(self) -> int: ...
@property
def period(self) -> int: ...
class BollingerBandwidth:
def __init__(self, period: int = 20, multiplier: float = 2.0) -> None: ...
def update(self, value: float) -> Optional[float]: ...
bindings/python/src/lib.rs
+226
View File
@@ -4103,6 +4103,228 @@ impl PyVerticalHorizontalFilter {
}
}
// ============================== True Range ==============================
#[pyclass(name = "TrueRange", module = "wickra._wickra")]
#[derive(Clone)]
struct PyTrueRange {
inner: wc::TrueRange,
}
#[pymethods]
impl PyTrueRange {
#[new]
fn new() -> Self {
Self {
inner: wc::TrueRange::new(),
}
}
fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<f64>> {
let c = extract_candle(candle)?;
Ok(self.inner.update(c))
}
/// Batch over numpy columns high, low, close (all equal length).
fn batch<'py>(
&mut self,
py: Python<'py>,
high: PyReadonlyArray1<'py, f64>,
low: PyReadonlyArray1<'py, f64>,
close: PyReadonlyArray1<'py, f64>,
) -> PyResult<Bound<'py, PyArray1<f64>>> {
let h = high
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
let l = low
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
let c = close
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
if h.len() != l.len() || l.len() != c.len() {
return Err(PyValueError::new_err(
"high, low, close must be equal length",
));
}
let mut out = Vec::with_capacity(h.len());
for i in 0..h.len() {
let candle = wc::Candle::new(c[i], h[i], l[i], c[i], 0.0, 0).map_err(map_err)?;
out.push(self.inner.update(candle).unwrap_or(f64::NAN));
}
Ok(out.into_pyarray_bound(py))
}
fn reset(&mut self) {
self.inner.reset();
}
fn is_ready(&self) -> bool {
self.inner.is_ready()
}
fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
fn __repr__(&self) -> String {
"TrueRange()".to_string()
}
}
// ============================== Chaikin Volatility ==============================
#[pyclass(name = "ChaikinVolatility", module = "wickra._wickra")]
#[derive(Clone)]
struct PyChaikinVolatility {
inner: wc::ChaikinVolatility,
}
#[pymethods]
impl PyChaikinVolatility {
#[new]
#[pyo3(signature = (ema_period=10, roc_period=10))]
fn new(ema_period: usize, roc_period: usize) -> PyResult<Self> {
Ok(Self {
inner: wc::ChaikinVolatility::new(ema_period, roc_period).map_err(map_err)?,
})
}
fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<f64>> {
let c = extract_candle(candle)?;
Ok(self.inner.update(c))
}
/// Batch over numpy columns high, low (both equal length).
fn batch<'py>(
&mut self,
py: Python<'py>,
high: PyReadonlyArray1<'py, f64>,
low: PyReadonlyArray1<'py, f64>,
) -> PyResult<Bound<'py, PyArray1<f64>>> {
let h = high
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
let l = low
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
if h.len() != l.len() {
return Err(PyValueError::new_err("high and low must be equal length"));
}
let mut out = Vec::with_capacity(h.len());
for i in 0..h.len() {
let candle = wc::Candle::new(l[i], h[i], l[i], l[i], 0.0, 0).map_err(map_err)?;
out.push(self.inner.update(candle).unwrap_or(f64::NAN));
}
Ok(out.into_pyarray_bound(py))
}
#[getter]
fn periods(&self) -> (usize, usize) {
self.inner.periods()
}
fn reset(&mut self) {
self.inner.reset();
}
fn is_ready(&self) -> bool {
self.inner.is_ready()
}
fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
fn __repr__(&self) -> String {
let (ema, roc) = self.inner.periods();
format!("ChaikinVolatility(ema_period={ema}, roc_period={roc})")
}
}
// ============================== Z-Score ==============================
#[pyclass(name = "ZScore", module = "wickra._wickra")]
#[derive(Clone)]
struct PyZScore {
inner: wc::ZScore,
}
#[pymethods]
impl PyZScore {
#[new]
#[pyo3(signature = (period=20))]
fn new(period: usize) -> PyResult<Self> {
Ok(Self {
inner: wc::ZScore::new(period).map_err(map_err)?,
})
}
fn update(&mut self, value: f64) -> Option<f64> {
self.inner.update(value)
}
fn batch<'py>(
&mut self,
py: Python<'py>,
prices: PyReadonlyArray1<'py, f64>,
) -> PyResult<Bound<'py, PyArray1<f64>>> {
let slice = prices
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
Ok(flatten(self.inner.batch(slice)).into_pyarray_bound(py))
}
#[getter]
fn period(&self) -> usize {
self.inner.period()
}
fn reset(&mut self) {
self.inner.reset();
}
fn is_ready(&self) -> bool {
self.inner.is_ready()
}
fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
fn __repr__(&self) -> String {
format!("ZScore(period={})", self.inner.period())
}
}
// ============================== Linear Regression Angle ==============================
#[pyclass(name = "LinRegAngle", module = "wickra._wickra")]
#[derive(Clone)]
struct PyLinRegAngle {
inner: wc::LinRegAngle,
}
#[pymethods]
impl PyLinRegAngle {
#[new]
#[pyo3(signature = (period=14))]
fn new(period: usize) -> PyResult<Self> {
Ok(Self {
inner: wc::LinRegAngle::new(period).map_err(map_err)?,
})
}
fn update(&mut self, value: f64) -> Option<f64> {
self.inner.update(value)
}
fn batch<'py>(
&mut self,
py: Python<'py>,
prices: PyReadonlyArray1<'py, f64>,
) -> PyResult<Bound<'py, PyArray1<f64>>> {
let slice = prices
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
Ok(flatten(self.inner.batch(slice)).into_pyarray_bound(py))
}
#[getter]
fn period(&self) -> usize {
self.inner.period()
}
fn reset(&mut self) {
self.inner.reset();
}
fn is_ready(&self) -> bool {
self.inner.is_ready()
}
fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
fn __repr__(&self) -> String {
format!("LinRegAngle(period={})", self.inner.period())
}
}
// ============================== Module ==============================
#[pymodule]
@@ -4175,5 +4397,9 @@ fn _wickra(_py: Python<'_>, m: &Bound<'_, PyModule>) -> PyResult<()> {
m.add_class::<PyBalanceOfPower>()?;
m.add_class::<PyChoppinessIndex>()?;
m.add_class::<PyVerticalHorizontalFilter>()?;
m.add_class::<PyTrueRange>()?;
m.add_class::<PyChaikinVolatility>()?;
m.add_class::<PyZScore>()?;
m.add_class::<PyLinRegAngle>()?;
Ok(())
}
bindings/wasm/src/lib.rs
+80
View File
@@ -95,6 +95,8 @@ wasm_scalar_indicator!(WasmPercentB, "PercentB", wc::PercentB, period: usize, mu
wasm_scalar_indicator!(WasmLinearRegression, "LinearRegression", wc::LinearRegression, period: usize);
wasm_scalar_indicator!(WasmLinRegSlope, "LinRegSlope", wc::LinRegSlope, period: usize);
wasm_scalar_indicator!(WasmVerticalHorizontalFilter, "VerticalHorizontalFilter", wc::VerticalHorizontalFilter, period: usize);
wasm_scalar_indicator!(WasmZScore, "ZScore", wc::ZScore, period: usize);
wasm_scalar_indicator!(WasmLinRegAngle, "LinRegAngle", wc::LinRegAngle, period: usize);
// ---------- KAMA (three params) ----------
@@ -1100,6 +1102,84 @@ impl WasmChoppinessIndex {
}
}
#[wasm_bindgen(js_name = TrueRange)]
pub struct WasmTrueRange {
inner: wc::TrueRange,
}
impl Default for WasmTrueRange {
fn default() -> Self {
Self::new()
}
}
#[wasm_bindgen(js_class = TrueRange)]
impl WasmTrueRange {
#[wasm_bindgen(constructor)]
pub fn new() -> WasmTrueRange {
Self {
inner: wc::TrueRange::new(),
}
}
pub fn update(&mut self, high: f64, low: f64, close: f64) -> Result<Option<f64>, JsError> {
let c = make_candle(high, low, close, 0.0)?;
Ok(self.inner.update(c))
}
pub fn batch(
&mut self,
high: &[f64],
low: &[f64],
close: &[f64],
) -> Result<Float64Array, JsError> {
let n = high.len();
if low.len() != n || close.len() != n {
return Err(JsError::new("high, low, close must be equal length"));
}
let mut out = Vec::with_capacity(n);
for i in 0..n {
let c = make_candle(high[i], low[i], close[i], 0.0)?;
out.push(self.inner.update(c).unwrap_or(f64::NAN));
}
Ok(Float64Array::from(out.as_slice()))
}
pub fn reset(&mut self) {
self.inner.reset();
}
}
#[wasm_bindgen(js_name = ChaikinVolatility)]
pub struct WasmChaikinVolatility {
inner: wc::ChaikinVolatility,
}
#[wasm_bindgen(js_class = ChaikinVolatility)]
impl WasmChaikinVolatility {
#[wasm_bindgen(constructor)]
pub fn new(ema_period: usize, roc_period: usize) -> Result<WasmChaikinVolatility, JsError> {
Ok(Self {
inner: wc::ChaikinVolatility::new(ema_period, roc_period).map_err(map_err)?,
})
}
pub fn update(&mut self, high: f64, low: f64) -> Result<Option<f64>, JsError> {
let c = make_candle(high, low, low, 0.0)?;
Ok(self.inner.update(c))
}
pub fn batch(&mut self, high: &[f64], low: &[f64]) -> Result<Float64Array, JsError> {
if high.len() != low.len() {
return Err(JsError::new("high and low must be equal length"));
}
let mut out = Vec::with_capacity(high.len());
for i in 0..high.len() {
let c = make_candle(high[i], low[i], low[i], 0.0)?;
out.push(self.inner.update(c).unwrap_or(f64::NAN));
}
Ok(Float64Array::from(out.as_slice()))
}
pub fn reset(&mut self) {
self.inner.reset();
}
}
#[wasm_bindgen(js_name = NATR)]
pub struct WasmNatr {
inner: wc::Natr,