Deepen Moving Averages family with seven additions (#177)
Deepens the **Moving Averages** family with seven widely-used variants (396 → 403 indicators), the first batch of Part B (family deepening). All are scalar `f64 → f64`: | Indicator | Binding | Notes | |-----------|---------|-------| | `SineWeightedMa` | `SWMA` | symmetric half-cycle sine-weighted window | | `GeometricMa` | `GMA` | rolling geometric mean (log-space average) | | `Ehma` | `EHMA` | exponential Hull MA (Hull construction over EMAs) | | `MedianMa` | `MedianMA` | rolling median, robust to single outliers | | `AdaptiveLaguerreFilter` | `AdaptiveLaguerre` | Ehlers' adaptive Laguerre filter (median-of-normalised-error γ) | | `GeneralizedDema` | `GD` | Tillson's volume-factor double EMA; `v=1` is DEMA, `v=0` is EMA | | `HoltWinters` | `HoltWinters` | Holt's linear double exponential smoothing (level + trend) | LSMA was dropped from the planned set: it already ships as `LinearRegression` (TA-Lib `LINEARREG`, the rolling least-squares endpoint). The five single-period filters use the generated scalar macro bindings; `GeneralizedDema` (period, v) and `HoltWinters` (alpha, beta) use hand-written node/python bindings with the typed wasm macro (precedent `T3` / `Alma`). Full coverage: core modules with per-branch unit tests (100% intent), mod/lib catalogue, FAMILIES group + assert, README + docs counters, CHANGELOG, all three bindings (regenerated `index.d.ts` / `index.js`), fuzz drivers, and the python/node test registries. Local verification: `cargo test -p wickra-core` (lib 3255 + doc 361), `cargo clippy --workspace --all-targets --all-features -D warnings` clean, node `npm run build && npm test` (478), python `pytest` (791).
This commit is contained in:
kingchenc
@@ -2354,6 +2354,250 @@ impl PyExpectancy {
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}
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}
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// ============================== SineWeightedMa ==============================
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#[pyclass(name = "SWMA", module = "wickra._wickra", skip_from_py_object)]
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#[derive(Clone)]
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struct PySineWeightedMa {
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inner: wc::SineWeightedMa,
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}
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#[pymethods]
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impl PySineWeightedMa {
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#[new]
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#[pyo3(signature = (period=14))]
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fn new(period: usize) -> PyResult<Self> {
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Ok(Self {
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inner: wc::SineWeightedMa::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!("SWMA(period={})", self.inner.period())
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}
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}
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// ============================== GeometricMa ==============================
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#[pyclass(name = "GMA", module = "wickra._wickra", skip_from_py_object)]
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#[derive(Clone)]
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struct PyGeometricMa {
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inner: wc::GeometricMa,
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}
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#[pymethods]
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impl PyGeometricMa {
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#[new]
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#[pyo3(signature = (period=14))]
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fn new(period: usize) -> PyResult<Self> {
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Ok(Self {
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inner: wc::GeometricMa::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!("GMA(period={})", self.inner.period())
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}
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}
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// ============================== Ehma ==============================
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#[pyclass(name = "EHMA", module = "wickra._wickra", skip_from_py_object)]
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#[derive(Clone)]
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struct PyEhma {
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inner: wc::Ehma,
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}
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#[pymethods]
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impl PyEhma {
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#[new]
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#[pyo3(signature = (period=9))]
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fn new(period: usize) -> PyResult<Self> {
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Ok(Self {
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inner: wc::Ehma::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!("EHMA(period={})", self.inner.period())
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}
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}
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// ============================== MedianMa ==============================
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#[pyclass(name = "MedianMA", module = "wickra._wickra", skip_from_py_object)]
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#[derive(Clone)]
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struct PyMedianMa {
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inner: wc::MedianMa,
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}
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#[pymethods]
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impl PyMedianMa {
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#[new]
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#[pyo3(signature = (period=14))]
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fn new(period: usize) -> PyResult<Self> {
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Ok(Self {
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inner: wc::MedianMa::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!("MedianMA(period={})", self.inner.period())
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}
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}
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// ============================== AdaptiveLaguerreFilter ==============================
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#[pyclass(
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name = "AdaptiveLaguerre",
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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 PyAdaptiveLaguerreFilter {
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inner: wc::AdaptiveLaguerreFilter,
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}
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#[pymethods]
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impl PyAdaptiveLaguerreFilter {
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#[new]
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#[pyo3(signature = (period=13))]
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fn new(period: usize) -> PyResult<Self> {
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Ok(Self {
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inner: wc::AdaptiveLaguerreFilter::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!("AdaptiveLaguerre(period={})", self.inner.period())
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}
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}
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// ============================== Stochastic ==============================
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#[pyclass(name = "Stochastic", module = "wickra._wickra", skip_from_py_object)]
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@@ -6197,6 +6441,130 @@ impl PyT3 {
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}
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}
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// ============================== GD ==============================
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#[pyclass(name = "GD", module = "wickra._wickra", skip_from_py_object)]
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#[derive(Clone)]
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struct PyGeneralizedDema {
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inner: wc::GeneralizedDema,
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}
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#[pymethods]
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impl PyGeneralizedDema {
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#[new]
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#[pyo3(signature = (period, v=0.7))]
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fn new(period: usize, v: f64) -> PyResult<Self> {
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Ok(Self {
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inner: wc::GeneralizedDema::new(period, v).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 slice = 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(slice)).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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#[getter]
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fn volume_factor(&self) -> f64 {
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self.inner.volume_factor()
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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!(
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"GD(period={}, v={})",
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self.inner.period(),
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self.inner.volume_factor()
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)
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}
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}
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// ============================== HoltWinters ==============================
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#[pyclass(name = "HoltWinters", module = "wickra._wickra", skip_from_py_object)]
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#[derive(Clone)]
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struct PyHoltWinters {
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inner: wc::HoltWinters,
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}
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#[pymethods]
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impl PyHoltWinters {
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#[new]
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#[pyo3(signature = (alpha=0.2, beta=0.1))]
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fn new(alpha: f64, beta: f64) -> PyResult<Self> {
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Ok(Self {
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inner: wc::HoltWinters::new(alpha, beta).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 slice = 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(slice)).into_pyarray(py))
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}
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#[getter]
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fn alpha(&self) -> f64 {
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self.inner.alpha()
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}
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#[getter]
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fn beta(&self) -> f64 {
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self.inner.beta()
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}
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#[getter]
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fn level(&self) -> Option<f64> {
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self.inner.level()
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}
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#[getter]
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fn trend(&self) -> Option<f64> {
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self.inner.trend()
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}
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#[getter]
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fn value(&self) -> Option<f64> {
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self.inner.value()
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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!(
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"HoltWinters(alpha={}, beta={})",
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self.inner.alpha(),
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self.inner.beta()
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)
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}
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}
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// ============================== VWMA ==============================
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#[pyclass(name = "VWMA", module = "wickra._wickra", skip_from_py_object)]
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@@ -19667,6 +20035,8 @@ fn _wickra(_py: Python<'_>, m: &Bound<'_, PyModule>) -> PyResult<()> {
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m.add_class::<PyTrima>()?;
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m.add_class::<PyZlema>()?;
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m.add_class::<PyT3>()?;
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m.add_class::<PyGeneralizedDema>()?;
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m.add_class::<PyHoltWinters>()?;
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m.add_class::<PyVwma>()?;
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m.add_class::<PyMom>()?;
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m.add_class::<PyCmo>()?;
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@@ -20031,5 +20401,10 @@ fn _wickra(_py: Python<'_>, m: &Bound<'_, PyModule>) -> PyResult<()> {
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m.add_class::<PyRegimeLabel>()?;
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m.add_class::<PyWinRate>()?;
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m.add_class::<PyExpectancy>()?;
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m.add_class::<PySineWeightedMa>()?;
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m.add_class::<PyGeometricMa>()?;
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m.add_class::<PyEhma>()?;
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m.add_class::<PyMedianMa>()?;
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m.add_class::<PyAdaptiveLaguerreFilter>()?;
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Ok(())
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}
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Reference in New Issue
Block a user