feat(indicators): B3 Trend & Directional batch (413 -> 420) (#181)
Adds the **B3 — Trend & Directional** batch: seven new indicators, taking the catalog from 413 to 420 (Trend & Directional family). | Indicator | Input → Output | Summary | |-----------|----------------|---------| | `Qstick` | candle → f64 | Chande's SMA of the candle body (close − open) | | `TtmTrend` | candle → f64 (±1) | John Carter close-vs-median-SMA trend filter | | `TrendStrengthIndex` | f64 → f64 | signed r² of an OLS regression of price vs time | | `PolarizedFractalEfficiency` | f64 → f64 | Hannula directional trend efficiency | | `WavePm` | f64 → f64 | Kase variance-normalised peak-momentum statistic (reconstruction) | | `GatorOscillator` | candle → struct | Bill Williams Alligator convergence/divergence histogram | | `KasePermissionStochastic` | candle → struct | double-smoothed stochastic permission filter | Note: the roadmap's "Directional Indicator +DI/−DI" item is already covered by the existing standalone `PlusDi` / `MinusDi` / `Dx`, so it is intentionally not re-added. All touchpoints wired: core (every-branch unit tests), Python/Node/WASM bindings, fuzz drivers, Python test registries + reference tests, Node factories, README/CHANGELOG counters. Local verify: `cargo test -p wickra-core` (lib 3389 + doc 378), `cargo clippy --workspace --all-targets --all-features -- -D warnings`, node build + 495 tests, maturin + 815 pytest, counter 420 == 420.
This commit is contained in:
kingchenc
@@ -2866,6 +2866,435 @@ impl PyStochasticCci {
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}
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}
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// ============================== TtmTrend ==============================
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#[pyclass(name = "TTM_TREND", module = "wickra._wickra", skip_from_py_object)]
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#[derive(Clone)]
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struct PyTtmTrend {
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inner: wc::TtmTrend,
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}
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#[pymethods]
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impl PyTtmTrend {
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#[new]
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#[pyo3(signature = (period=6))]
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fn new(period: usize) -> PyResult<Self> {
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Ok(Self {
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inner: wc::TtmTrend::new(period).map_err(map_err)?,
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})
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}
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fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<f64>> {
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let c = extract_candle(candle)?;
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Ok(self.inner.update(c))
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}
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/// Batch over numpy columns: high, low, close (all 1-D, equal length).
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fn batch<'py>(
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&mut self,
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py: Python<'py>,
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high: PyReadonlyArray1<'py, f64>,
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low: PyReadonlyArray1<'py, f64>,
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close: PyReadonlyArray1<'py, f64>,
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) -> PyResult<Bound<'py, PyArray1<f64>>> {
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let h = high
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.as_slice()
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.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
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let l = low
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.as_slice()
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.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
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let c = close
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.as_slice()
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.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
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if h.len() != l.len() || l.len() != c.len() {
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return Err(PyValueError::new_err(
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"high, low, close must be equal length",
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));
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}
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let mut out = Vec::with_capacity(h.len());
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for i in 0..h.len() {
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let candle = wc::Candle::new(c[i], h[i], l[i], c[i], 0.0, 0).map_err(map_err)?;
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out.push(self.inner.update(candle).unwrap_or(f64::NAN));
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}
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Ok(out.into_pyarray(py))
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}
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#[getter]
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fn period(&self) -> usize {
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self.inner.period()
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}
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fn reset(&mut self) {
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self.inner.reset();
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}
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fn is_ready(&self) -> bool {
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self.inner.is_ready()
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}
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fn warmup_period(&self) -> usize {
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self.inner.warmup_period()
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}
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fn __repr__(&self) -> String {
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format!("TTM_TREND(period={})", self.inner.period())
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}
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}
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// ============================== TrendStrengthIndex ==============================
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#[pyclass(
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name = "TREND_STRENGTH_INDEX",
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module = "wickra._wickra",
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skip_from_py_object
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)]
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#[derive(Clone)]
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struct PyTrendStrengthIndex {
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inner: wc::TrendStrengthIndex,
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}
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#[pymethods]
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impl PyTrendStrengthIndex {
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#[new]
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#[pyo3(signature = (period=20))]
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fn new(period: usize) -> PyResult<Self> {
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Ok(Self {
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inner: wc::TrendStrengthIndex::new(period).map_err(map_err)?,
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})
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}
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fn update(&mut self, value: f64) -> Option<f64> {
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self.inner.update(value)
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}
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fn batch<'py>(
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&mut self,
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py: Python<'py>,
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prices: PyReadonlyArray1<'py, f64>,
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) -> PyResult<Bound<'py, PyArray1<f64>>> {
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let s = prices
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.as_slice()
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.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
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Ok(flatten(self.inner.batch(s)).into_pyarray(py))
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}
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#[getter]
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fn period(&self) -> usize {
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self.inner.period()
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}
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fn reset(&mut self) {
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self.inner.reset();
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}
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fn is_ready(&self) -> bool {
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self.inner.is_ready()
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}
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fn warmup_period(&self) -> usize {
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self.inner.warmup_period()
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}
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fn __repr__(&self) -> String {
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format!("TREND_STRENGTH_INDEX(period={})", self.inner.period())
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}
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}
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// ============================== Qstick ==============================
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#[pyclass(name = "Qstick", module = "wickra._wickra", skip_from_py_object)]
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#[derive(Clone)]
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struct PyQstick {
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inner: wc::Qstick,
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}
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#[pymethods]
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impl PyQstick {
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#[new]
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#[pyo3(signature = (period=10))]
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fn new(period: usize) -> PyResult<Self> {
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Ok(Self {
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inner: wc::Qstick::new(period).map_err(map_err)?,
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})
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}
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fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<f64>> {
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let c = extract_candle(candle)?;
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Ok(self.inner.update(c))
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}
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/// Batch over open/close numpy columns (Qstick reads the body close-open).
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fn batch<'py>(
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&mut self,
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py: Python<'py>,
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open: PyReadonlyArray1<'py, f64>,
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close: PyReadonlyArray1<'py, f64>,
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) -> PyResult<Bound<'py, PyArray1<f64>>> {
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let o = open
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.as_slice()
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.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
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let c = close
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.as_slice()
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.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
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if o.len() != c.len() {
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return Err(PyValueError::new_err("open, close must be equal length"));
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}
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let n = o.len();
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let mut out = Vec::with_capacity(n);
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for i in 0..n {
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let hi = o[i].max(c[i]);
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let lo = o[i].min(c[i]);
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let candle = wc::Candle::new(o[i], hi, lo, c[i], 0.0, 0).map_err(map_err)?;
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out.push(self.inner.update(candle).unwrap_or(f64::NAN));
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}
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Ok(out.into_pyarray(py))
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}
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#[getter]
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fn period(&self) -> usize {
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self.inner.period()
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}
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fn reset(&mut self) {
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self.inner.reset();
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}
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fn is_ready(&self) -> bool {
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self.inner.is_ready()
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}
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fn warmup_period(&self) -> usize {
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self.inner.warmup_period()
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}
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}
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// ============================== PolarizedFractalEfficiency ==============================
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#[pyclass(
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name = "POLARIZED_FRACTAL_EFFICIENCY",
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module = "wickra._wickra",
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skip_from_py_object
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)]
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#[derive(Clone)]
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struct PyPolarizedFractalEfficiency {
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inner: wc::PolarizedFractalEfficiency,
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}
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#[pymethods]
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impl PyPolarizedFractalEfficiency {
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#[new]
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#[pyo3(signature = (period=10, smoothing=5))]
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fn new(period: usize, smoothing: usize) -> PyResult<Self> {
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Ok(Self {
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inner: wc::PolarizedFractalEfficiency::new(period, smoothing).map_err(map_err)?,
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})
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}
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fn update(&mut self, value: f64) -> Option<f64> {
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self.inner.update(value)
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}
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fn batch<'py>(
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&mut self,
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py: Python<'py>,
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prices: PyReadonlyArray1<'py, f64>,
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) -> PyResult<Bound<'py, PyArray1<f64>>> {
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let s = prices
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.as_slice()
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.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
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Ok(flatten(self.inner.batch(s)).into_pyarray(py))
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}
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#[getter]
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fn period(&self) -> usize {
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self.inner.periods().0
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}
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#[getter]
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fn smoothing(&self) -> usize {
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self.inner.periods().1
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}
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fn reset(&mut self) {
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self.inner.reset();
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}
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fn is_ready(&self) -> bool {
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self.inner.is_ready()
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}
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fn warmup_period(&self) -> usize {
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self.inner.warmup_period()
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}
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}
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// ============================== WavePm ==============================
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#[pyclass(name = "WAVE_PM", module = "wickra._wickra", skip_from_py_object)]
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#[derive(Clone)]
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struct PyWavePm {
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inner: wc::WavePm,
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}
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#[pymethods]
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impl PyWavePm {
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#[new]
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#[pyo3(signature = (length=32, smoothing=3))]
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fn new(length: usize, smoothing: usize) -> PyResult<Self> {
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Ok(Self {
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inner: wc::WavePm::new(length, smoothing).map_err(map_err)?,
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})
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}
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fn update(&mut self, value: f64) -> Option<f64> {
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self.inner.update(value)
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}
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fn batch<'py>(
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&mut self,
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py: Python<'py>,
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prices: PyReadonlyArray1<'py, f64>,
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) -> PyResult<Bound<'py, PyArray1<f64>>> {
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let s = prices
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.as_slice()
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.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
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Ok(flatten(self.inner.batch(s)).into_pyarray(py))
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}
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#[getter]
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fn length(&self) -> usize {
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self.inner.periods().0
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}
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#[getter]
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fn smoothing(&self) -> usize {
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self.inner.periods().1
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}
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fn reset(&mut self) {
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self.inner.reset();
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}
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fn is_ready(&self) -> bool {
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self.inner.is_ready()
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}
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fn warmup_period(&self) -> usize {
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self.inner.warmup_period()
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}
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}
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// ============================== GatorOscillator ==============================
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#[pyclass(
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name = "GatorOscillator",
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module = "wickra._wickra",
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skip_from_py_object
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)]
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#[derive(Clone)]
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struct PyGatorOscillator {
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inner: wc::GatorOscillator,
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}
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#[pymethods]
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impl PyGatorOscillator {
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#[new]
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#[pyo3(signature = (jaw_period=13, teeth_period=8, lips_period=5))]
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fn new(jaw_period: usize, teeth_period: usize, lips_period: usize) -> PyResult<Self> {
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Ok(Self {
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inner: wc::GatorOscillator::new(jaw_period, teeth_period, lips_period)
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.map_err(map_err)?,
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})
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}
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fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<(f64, f64)>> {
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let c = extract_candle(candle)?;
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Ok(self.inner.update(c).map(|o| (o.upper, o.lower)))
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}
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/// Batch over high/low/close numpy columns. Returns shape `(n, 2)` for
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/// `[upper, lower]`.
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fn batch<'py>(
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||||
&mut self,
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py: Python<'py>,
|
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high: PyReadonlyArray1<'py, f64>,
|
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low: PyReadonlyArray1<'py, f64>,
|
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close: PyReadonlyArray1<'py, f64>,
|
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) -> PyResult<Bound<'py, PyArray2<f64>>> {
|
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let h = high
|
||||
.as_slice()
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.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
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let l = low
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.as_slice()
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.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
|
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let c = close
|
||||
.as_slice()
|
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.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
|
||||
if h.len() != l.len() || l.len() != c.len() {
|
||||
return Err(PyValueError::new_err(
|
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"high, low, close must be equal length",
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||||
));
|
||||
}
|
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let n = h.len();
|
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let mut out = vec![f64::NAN; n * 2];
|
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for i in 0..n {
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let candle = wc::Candle::new(c[i], h[i], l[i], c[i], 0.0, 0).map_err(map_err)?;
|
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if let Some(o) = self.inner.update(candle) {
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out[i * 2] = o.upper;
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out[i * 2 + 1] = o.lower;
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}
|
||||
}
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Ok(numpy::ndarray::Array2::from_shape_vec((n, 2), out)
|
||||
.expect("shape consistent")
|
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.into_pyarray(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()
|
||||
}
|
||||
}
|
||||
|
||||
// ============================== KasePermissionStochastic ==============================
|
||||
|
||||
#[pyclass(
|
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name = "KasePermissionStochastic",
|
||||
module = "wickra._wickra",
|
||||
skip_from_py_object
|
||||
)]
|
||||
#[derive(Clone)]
|
||||
struct PyKasePermissionStochastic {
|
||||
inner: wc::KasePermissionStochastic,
|
||||
}
|
||||
|
||||
#[pymethods]
|
||||
impl PyKasePermissionStochastic {
|
||||
#[new]
|
||||
#[pyo3(signature = (length=9, smooth=3))]
|
||||
fn new(length: usize, smooth: usize) -> PyResult<Self> {
|
||||
Ok(Self {
|
||||
inner: wc::KasePermissionStochastic::new(length, smooth).map_err(map_err)?,
|
||||
})
|
||||
}
|
||||
fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<(f64, f64)>> {
|
||||
let c = extract_candle(candle)?;
|
||||
Ok(self.inner.update(c).map(|o| (o.fast, o.slow)))
|
||||
}
|
||||
/// Batch over high/low/close numpy columns. Returns shape `(n, 2)` for
|
||||
/// `[fast, slow]`.
|
||||
fn batch<'py>(
|
||||
&mut self,
|
||||
py: Python<'py>,
|
||||
high: PyReadonlyArray1<'py, f64>,
|
||||
low: PyReadonlyArray1<'py, f64>,
|
||||
close: PyReadonlyArray1<'py, f64>,
|
||||
) -> PyResult<Bound<'py, PyArray2<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 n = h.len();
|
||||
let mut out = vec![f64::NAN; n * 2];
|
||||
for i in 0..n {
|
||||
let candle = wc::Candle::new(c[i], h[i], l[i], c[i], 0.0, 0).map_err(map_err)?;
|
||||
if let Some(o) = self.inner.update(candle) {
|
||||
out[i * 2] = o.fast;
|
||||
out[i * 2 + 1] = o.slow;
|
||||
}
|
||||
}
|
||||
Ok(numpy::ndarray::Array2::from_shape_vec((n, 2), out)
|
||||
.expect("shape consistent")
|
||||
.into_pyarray(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()
|
||||
}
|
||||
}
|
||||
|
||||
// ============================== Stochastic ==============================
|
||||
|
||||
#[pyclass(name = "IMI", module = "wickra._wickra", skip_from_py_object)]
|
||||
@@ -20986,5 +21415,12 @@ fn _wickra(_py: Python<'_>, m: &Bound<'_, PyModule>) -> PyResult<()> {
|
||||
m.add_class::<PyRsx>()?;
|
||||
m.add_class::<PyDynamicMomentumIndex>()?;
|
||||
m.add_class::<PyStochasticCci>()?;
|
||||
m.add_class::<PyTtmTrend>()?;
|
||||
m.add_class::<PyTrendStrengthIndex>()?;
|
||||
m.add_class::<PyQstick>()?;
|
||||
m.add_class::<PyPolarizedFractalEfficiency>()?;
|
||||
m.add_class::<PyWavePm>()?;
|
||||
m.add_class::<PyGatorOscillator>()?;
|
||||
m.add_class::<PyKasePermissionStochastic>()?;
|
||||
Ok(())
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user