kingchencandGitHub
d9d3ad18aa
* feat(apo): add Absolute Price Oscillator EMA(close, fast) - EMA(close, slow). Like MACD without the signal EMA. Defaults to (fast = 12, slow = 26); fast must be strictly less than slow. Touchpoints: apo.rs + mod.rs + lib.rs re-export, PyApo + __init__.py + test_new_indicators SCALAR + test_known_values flat reference, ApoNode + index.d.ts/index.js + indicators.test.js factory + reference, WasmApo via scalar macro, scalar-fuzz target, README + CHANGELOG. * fix(apo): add PyApo + ApoNode + WasmApo bindings missed fromec269d8The previous APO commit (ec269d8) only registered APO in the Python __init__.py / Node index.js / Node index.d.ts / fuzz / tests / docs. The actual PyApo pyclass, ApoNode napi class, and WasmApo wasm class edits silently no-op'd because the underlying lib.rs files had been touched by a branch switch between Read and Edit. The bindings were therefore advertising APO from the Python module / Node package / WASM module but not actually exposing it. Fix: insert PyApo block + add_class call in bindings/python/src/lib.rs, ApoNode block in bindings/node/src/lib.rs, WasmApo macro line in bindings/wasm/src/lib.rs. cargo test workspace stays at 615 (no new tests added; the existing test_known_values + indicators.test.js references would have failed at import once the bindings rebuilt without these classes). * feat(ao-histogram): add Awesome Oscillator Histogram AO - SMA(AO, sma_period). A configurable variant of the existing AcceleratorOscillator (which fixes fast=5, slow=34, sma=5). Three parameters; defaults match Bill Williams' Accelerator. Touchpoints: awesome_oscillator_histogram.rs + mod.rs + lib.rs re-export, PyAoHist + __init__.py + test_new_indicators CANDLE_SCALAR + test_known_values flat reference, AwesomeOscillatorHistogramNode + index.d.ts/index.js + indicators.test.js factory + reference, WasmAoHist, candle-fuzz target, README + CHANGELOG. * feat(cfo): add Chande Forecast Oscillator 100 * (close - LinReg(close, period)) / close. Positive when close overshoots the linear forecast, negative when it undershoots. Holds the previous value if the close is zero (percentage form undefined). Single param period (default 14). Touchpoints: cfo.rs + mod.rs + lib.rs re-export, PyCfo + __init__.py + test_new_indicators SCALAR + test_known_values linear reference, CfoNode + index.d.ts/index.js + indicators.test.js factory + reference, WasmCfo via scalar macro, scalar-fuzz target, README + CHANGELOG. * fix(cfo): add WasmCfo binding missed from733afd9* feat(zero-lag-macd): add Zero-Lag MACD Classic MACD topology with ZLEMA substituted for EMA everywhere: faster reaction to trend changes at the cost of slightly noisier readings. Multi-output ZeroLagMacdOutput { macd, signal, histogram }. Three parameters (fast = 12, slow = 26, signal = 9); fast must be strictly less than slow. Touchpoints: zero_lag_macd.rs + mod.rs + lib.rs re-export, PyZeroLagMacd + __init__.py + test_new_indicators MULTI + test_known_values flat reference, ZeroLagMacdNode + ZeroLagMacdValue + index.d.ts/index.js + indicators.test.js multi factory + reference, WasmZeroLagMacd, scalar fuzz with hand-rolled drive (multi-output bypasses the f64-only helper), README + CHANGELOG. * feat(elder-impulse): add Alexander Elder Impulse System Tri-state momentum gauge: +1 (green/buy) when EMA trend and MACD histogram both rise, -1 (red/sell) when both fall, 0 (blue/neutral) on disagreement. Four parameters (ema_period, macd_fast, macd_slow, macd_signal); defaults (13, 12, 26, 9) match Elder. Internally feeds both branches on every input so they warm in parallel; needs one bar past the slowest branch to seed direction state. Touchpoints: elder_impulse.rs + mod.rs + lib.rs re-export, PyElderImpulse + __init__.py + test_new_indicators SCALAR + test_known_values neutral reference, ElderImpulseNode + index.d.ts/index.js + indicators.test.js factory + reference, WasmElderImpulse via scalar macro, scalar-fuzz target, README + CHANGELOG. * feat(stc): add Schaff Trend Cycle Doug Schaff's doubly-Stochastic-smoothed MACD. Bounded [0, 100] reading that reacts faster than MACD by extracting the percentile of MACD within a recent window, half-EMA-smoothing it, and re-stochasing the smoothed series. Four parameters (fast = 23, slow = 50, schaff_period = 10, factor = 0.5); fast must be strictly less than slow and factor must lie in (0, 1]. Output clamped to [0, 100] to absorb floating-point rounding. The stochastic stages clamp to 0 when their rolling range collapses (flat input or perfectly monotone trend), so a flat series settles deterministically at 0 after warmup. Touchpoints: stc.rs + mod.rs + lib.rs re-export, PyStc + __init__.py + test_new_indicators SCALAR + test_known_values flat reference, StcNode + index.d.ts/index.js + indicators.test.js factory + reference, WasmStc via scalar macro, scalar-fuzz target, README + CHANGELOG. * fix(stc): rename last_stc -> last_value to satisfy clippy * ci: Retry setup-node and setup-python on CDN flakes Setup-node on Windows runners and setup-python across all OSes occasionally fail with a silent hang or 5xx mid-download ("Attempting to download 18..." → fail in <1s) — pure upstream CDN flake. The fix ran on this branch's previous merge commit (24e723f) had to be re-triggered manually via `gh run rerun --failed`. Wrap both setup actions with continue-on-error and a follow-up retry step that waits 30s and re-runs the same setup. The retry only fires when the first attempt failed (steps.<id>.outcome == 'failure'), so a green setup costs nothing extra. The retry uses the identical pinned SHA so we still get supply-chain verification on both attempts. Applied to ci.yml (Python matrix and Node matrix). release.yml has the same setup-node / setup-python steps but is rarely re-run, so the existing manual rerun pattern stays sufficient for now. * test(zero-lag-macd): Fix MULTI dict shape mismatch + cover warmup_period ZeroLagMACD was registered in the Python MULTI dict (which asserts a (n, 2) batch shape) but actually emits (n, 3) — macd, signal, histogram — like MACD. Moved out into its own standalone test test_zero_lag_macd_streaming_matches_batch (3-tuple shape), and included in the lifecycle sweep. Mirrors the existing Alligator pattern for 3-output candle indicators. Also adds a unit test for ZeroLagMacd::warmup_period that pins both the (12, 26, 9) classic case and a small-period config — these four lines were the codecov/patch miss on PR 41.
64 lines
2.8 KiB
Rust
64 lines
2.8 KiB
Rust
//! `wickra-core`: streaming-first technical indicators.
|
|
//!
|
|
//! The core engine of Wickra. Every indicator is implemented as a state machine
|
|
//! that consumes inputs one at a time via [`Indicator::update`] in constant time.
|
|
//! Batch evaluation is provided as a blanket extension trait so the same code
|
|
//! path serves both online (tick-by-tick) and offline (historical) workloads.
|
|
//!
|
|
//! # Design
|
|
//!
|
|
//! - **Streaming-first.** State is held by the indicator instance, so a new value
|
|
//! only re-computes deltas, not the whole series.
|
|
//! - **Batch is free.** [`BatchExt::batch`] is a blanket implementation that
|
|
//! simply replays `update` over a slice. Writing one implementation gives both
|
|
//! APIs.
|
|
//! - **Composable.** Indicators implement [`Indicator<Input = f64, Output = f64>`]
|
|
//! wherever they conceptually take a price, so they can be chained via
|
|
//! [`Chain`].
|
|
//! - **No `unsafe`.** The crate forbids `unsafe_code` in the workspace lints.
|
|
//!
|
|
//! # Quick start
|
|
//!
|
|
//! ```
|
|
//! use wickra_core::{BatchExt, Indicator, Sma};
|
|
//!
|
|
//! // Streaming:
|
|
//! let mut sma = Sma::new(3).unwrap();
|
|
//! assert_eq!(sma.update(1.0), None);
|
|
//! assert_eq!(sma.update(2.0), None);
|
|
//! assert_eq!(sma.update(3.0), Some(2.0));
|
|
//!
|
|
//! // Batch (replays `update` internally):
|
|
//! let mut sma = Sma::new(3).unwrap();
|
|
//! let out = sma.batch(&[1.0, 2.0, 3.0, 4.0]);
|
|
//! assert_eq!(out, vec![None, None, Some(2.0), Some(3.0)]);
|
|
//! ```
|
|
|
|
#![cfg_attr(docsrs, feature(doc_cfg))]
|
|
|
|
mod error;
|
|
mod ohlcv;
|
|
mod traits;
|
|
|
|
pub mod indicators;
|
|
|
|
pub use error::{Error, Result};
|
|
pub use indicators::{
|
|
AcceleratorOscillator, Adl, Adx, AdxOutput, Alligator, AlligatorOutput, Alma, Apo, Aroon,
|
|
AroonOscillator, AroonOutput, Atr, AtrTrailingStop, AwesomeOscillator,
|
|
AwesomeOscillatorHistogram, BalanceOfPower, BollingerBands, BollingerBandwidth,
|
|
BollingerOutput, Cci, Cfo, ChaikinMoneyFlow, ChaikinOscillator, ChaikinVolatility,
|
|
ChandeKrollStop, ChandeKrollStopOutput, ChandelierExit, ChandelierExitOutput, ChoppinessIndex,
|
|
Cmo, ConnorsRsi, Coppock, Dema, Donchian, DonchianOutput, Dpo, EaseOfMovement, ElderImpulse,
|
|
Ema, Evwma, ForceIndex, Frama, HistoricalVolatility, Hma, Inertia, Jma, Kama, Keltner,
|
|
KeltnerOutput, Kst, KstOutput, LaguerreRsi, LinRegAngle, LinRegSlope, LinearRegression,
|
|
MacdIndicator, MacdOutput, MassIndex, McGinleyDynamic, MedianPrice, Mfi, Mom, Natr, Obv,
|
|
PercentB, Pgo, Pmo, Ppo, Psar, Roc, RollingVwap, Rsi, Rvi, Sma, Smi, Smma, Stc, StdDev,
|
|
StochRsi, Stochastic, StochasticOutput, SuperTrend, SuperTrendOutput, Tema, Trima, Trix,
|
|
TrueRange, Tsi, TypicalPrice, UlcerIndex, UltimateOscillator, VerticalHorizontalFilter, Vidya,
|
|
VolumePriceTrend, Vortex, VortexOutput, Vwap, Vwma, WeightedClose, WilliamsR, Wma, ZScore,
|
|
ZeroLagMacd, ZeroLagMacdOutput, Zlema, T3,
|
|
};
|
|
pub use ohlcv::{Candle, Tick};
|
|
pub use traits::{BatchExt, Chain, Indicator};
|