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
2026-06-04 13:44:51 +02:00
committed by GitHub
parent 8dc7158912
commit b228a70d7d
21 changed files with 2492 additions and 55 deletions
+8 -1
View File
@@ -14,7 +14,7 @@
//! `Ema(20)`. This target now covers every scalar indicator in the catalogue.
use libfuzzer_sys::fuzz_target;
use wickra_core::{AdaptiveCycle, Alma, AnchoredRsi, Apo, Autocorrelation, AverageDrawdown, BatchExt, Beta, BollingerBands, CalmarRatio, CenterOfGravity, Cfo, Cmo, CoefficientOfVariation, ConditionalValueAtRisk, ConnorsRsi, Coppock, CyberneticCycle, Decycler, DecyclerOscillator, Dema, DetrendedStdDev, DoubleBollinger, Dpo, DrawdownDuration, EhlersStochastic, ElderImpulse, Ema, EmpiricalModeDecomposition, Expectancy, Fama, FisherTransform, Frama, GainLossRatio, HilbertDominantCycle, HistoricalVolatility, Hma, HtDcPhase, HtPhasor, HtTrendMode, HurstExponent, Indicator, InstantaneousTrendline, InverseFisherTransform, Jma, JumpIndicator, Kama, KellyCriterion, Kst, Kurtosis, LaguerreRsi, LinRegAngle, LinRegChannel, LinRegIntercept, LinRegSlope, LinearRegression, LogReturn, MaEnvelope, MaType, MacdExt, MacdFix, MacdIndicator, Mama, MaxDrawdown, McGinleyDynamic, MedianAbsoluteDeviation, MidPoint, Mom, OmegaRatio, PainIndex, PearsonCorrelation, PercentageTrailingStop, Pmo, Ppo, ProfitFactor, RSquared, RealizedVolatility, RecoveryFactor, RegimeLabel, RenkoTrailingStop, Roc, Rocp, Rocr, Rocr100, RollingIqr, RollingPercentileRank, RollingQuantile, RoofingFilter, Rsi, RviVolatility, SharpeRatio, SineWave, Skewness, Sma, Smma, SortinoRatio, SpearmanCorrelation, StandardError, StandardErrorBands, Stc, StdDev, StepTrailingStop, StochRsi, SuperSmoother, Tema, Tii, TrendLabel, Trima, Trix, Tsf, Tsi, UlcerIndex, ValueAtRisk, Variance, VerticalHorizontalFilter, Vidya, WinRate, Wma, ZScore, ZeroLagMacd, Zlema, T3};
use wickra_core::{AdaptiveCycle, AdaptiveLaguerreFilter, Alma, AnchoredRsi, Apo, Autocorrelation, AverageDrawdown, BatchExt, Beta, BollingerBands, CalmarRatio, CenterOfGravity, Cfo, Cmo, CoefficientOfVariation, ConditionalValueAtRisk, ConnorsRsi, Coppock, CyberneticCycle, Decycler, DecyclerOscillator, Dema, DetrendedStdDev, DoubleBollinger, Dpo, DrawdownDuration, EhlersStochastic, Ehma, ElderImpulse, Ema, EmpiricalModeDecomposition, Expectancy, Fama, FisherTransform, Frama, GainLossRatio, GeneralizedDema, GeometricMa, HilbertDominantCycle, HistoricalVolatility, Hma, HoltWinters, HtDcPhase, HtPhasor, HtTrendMode, HurstExponent, Indicator, InstantaneousTrendline, InverseFisherTransform, Jma, JumpIndicator, Kama, KellyCriterion, Kst, Kurtosis, LaguerreRsi, LinRegAngle, LinRegChannel, LinRegIntercept, LinRegSlope, LinearRegression, LogReturn, MaEnvelope, MaType, MacdExt, MacdFix, MacdIndicator, Mama, MaxDrawdown, McGinleyDynamic, MedianAbsoluteDeviation, MedianMa, MidPoint, Mom, OmegaRatio, PainIndex, PearsonCorrelation, PercentageTrailingStop, Pmo, Ppo, ProfitFactor, RSquared, RealizedVolatility, RecoveryFactor, RegimeLabel, RenkoTrailingStop, Roc, Rocp, Rocr, Rocr100, RollingIqr, RollingPercentileRank, RollingQuantile, RoofingFilter, Rsi, RviVolatility, SharpeRatio, SineWave, SineWeightedMa, Skewness, Sma, Smma, SortinoRatio, SpearmanCorrelation, StandardError, StandardErrorBands, Stc, StdDev, StepTrailingStop, StochRsi, SuperSmoother, Tema, Tii, TrendLabel, Trima, Trix, Tsf, Tsi, UlcerIndex, ValueAtRisk, Variance, VerticalHorizontalFilter, Vidya, WinRate, Wma, ZScore, ZeroLagMacd, Zlema, T3};
/// Drive a single streaming + batch run through one scalar indicator. Marked
/// `#[inline(never)]` so a panic backtrace pin-points the specific indicator.
@@ -43,6 +43,13 @@ fuzz_target!(|data: Vec<f64>| {
drive(|| Dema::new(14).unwrap(), &data);
drive(|| Tema::new(14).unwrap(), &data);
drive(|| Hma::new(14).unwrap(), &data);
drive(|| SineWeightedMa::new(14).unwrap(), &data);
drive(|| GeometricMa::new(14).unwrap(), &data);
drive(|| Ehma::new(9).unwrap(), &data);
drive(|| MedianMa::new(14).unwrap(), &data);
drive(|| AdaptiveLaguerreFilter::new(13).unwrap(), &data);
drive(|| GeneralizedDema::new(5, 0.7).unwrap(), &data);
drive(|| HoltWinters::new(0.2, 0.1).unwrap(), &data);
drive(|| Roc::new(14).unwrap(), &data);
drive(|| Rocp::new(14).unwrap(), &data);
drive(|| Rocr::new(14).unwrap(), &data);