F-Abschluss: wire the Python package, refresh docs and extend the test suites
Finalises the F1-F12 indicator expansion (25 -> 63 indicators). - Python `wickra/__init__.py`: import and re-export all 63 indicators, grouped by family, with a matching `__all__`. The package previously exposed only the original 25 even though the compiled module and the `.pyi` stubs already carried the rest. - Docs: `Home.md` and `README.md` indicator counts and family tables updated to 63; `Indicators-Overview.md` already restructured per family in F10-F12; `Warmup-Periods.md` gains all 38 new indicators across the single- and multi-output tables (and the stale two-arg `Psar::new` example is corrected to three args); `CHANGELOG.md` `[Unreleased]` lists every new indicator by family. - Tests: `bindings/node/__tests__/indicators.test.js` covers all 63 indicators (streaming==batch plus four new reference-value checks), 80/80 green; new `bindings/python/tests/test_new_indicators.py` covers the 38 additions (streaming==batch, shapes, reference values, lifecycle), Python suite 105/105 green. - `bindings/node/index.js` regenerated by `napi build`. cargo fmt + clippy (core/wickra/data/wasm/node) clean; 454 core tests, 25 data tests, 66 doctests, 80 Node tests and 105 Python tests green; `cargo check -p wickra-wasm --tests` green.
This commit is contained in:
kingchenc
@@ -1,5 +1,5 @@
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// Comprehensive tests for the Wickra Node bindings: streaming-vs-batch
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// equivalence, reference values, and lifecycle methods across all 25
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// equivalence, reference values, and lifecycle methods across all 63
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// indicators. Ported from the Python test_streaming_vs_batch / test_known_values
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// suites.
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@@ -36,6 +36,25 @@ const scalarFactories = {
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ROC: () => new wickra.ROC(12),
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TRIX: () => new wickra.TRIX(9),
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KAMA: () => new wickra.KAMA(10, 2, 30),
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SMMA: () => new wickra.SMMA(14),
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TRIMA: () => new wickra.TRIMA(20),
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ZLEMA: () => new wickra.ZLEMA(14),
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T3: () => new wickra.T3(5, 0.7),
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MOM: () => new wickra.MOM(10),
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CMO: () => new wickra.CMO(14),
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TSI: () => new wickra.TSI(25, 13),
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PMO: () => new wickra.PMO(35, 20),
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StochRSI: () => new wickra.StochRSI(14, 14),
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PPO: () => new wickra.PPO(12, 26),
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DPO: () => new wickra.DPO(20),
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Coppock: () => new wickra.Coppock(14, 11, 10),
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StdDev: () => new wickra.StdDev(20),
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UlcerIndex: () => new wickra.UlcerIndex(14),
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HistoricalVolatility: () => new wickra.HistoricalVolatility(20, 252),
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BollingerBandwidth: () => new wickra.BollingerBandwidth(20, 2),
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PercentB: () => new wickra.PercentB(20, 2),
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LinearRegression: () => new wickra.LinearRegression(14),
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LinRegSlope: () => new wickra.LinRegSlope(14),
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};
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for (const [name, make] of Object.entries(scalarFactories)) {
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@@ -61,6 +80,21 @@ const candleScalar = {
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VWAP: { make: () => new wickra.VWAP(), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
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AwesomeOscillator: { make: () => new wickra.AwesomeOscillator(5, 34), step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
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OBV: { make: () => new wickra.OBV(), step: (ind, i) => ind.update(close[i], volume[i]), batch: (ind) => ind.batch(close, volume) },
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VWMA: { make: () => new wickra.VWMA(20), step: (ind, i) => ind.update(close[i], volume[i]), batch: (ind) => ind.batch(close, volume) },
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UltimateOscillator: { make: () => new wickra.UltimateOscillator(7, 14, 28), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
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AroonOscillator: { make: () => new wickra.AroonOscillator(14), step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
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NATR: { make: () => new wickra.NATR(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
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MassIndex: { make: () => new wickra.MassIndex(9, 25), step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
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ADL: { make: () => new wickra.ADL(), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
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VolumePriceTrend: { make: () => new wickra.VolumePriceTrend(), step: (ind, i) => ind.update(close[i], volume[i]), batch: (ind) => ind.batch(close, volume) },
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ChaikinMoneyFlow: { make: () => new wickra.ChaikinMoneyFlow(20), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
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ChaikinOscillator: { make: () => new wickra.ChaikinOscillator(3, 10), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
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ForceIndex: { make: () => new wickra.ForceIndex(13), step: (ind, i) => ind.update(close[i], volume[i]), batch: (ind) => ind.batch(close, volume) },
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EaseOfMovement: { make: () => new wickra.EaseOfMovement(14, 1e8), step: (ind, i) => ind.update(high[i], low[i], volume[i]), batch: (ind) => ind.batch(high, low, volume) },
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AtrTrailingStop: { make: () => new wickra.AtrTrailingStop(14, 3), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
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TypicalPrice: { make: () => new wickra.TypicalPrice(), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
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MedianPrice: { make: () => new wickra.MedianPrice(), step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
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WeightedClose: { make: () => new wickra.WeightedClose(), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
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};
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for (const [name, d] of Object.entries(candleScalar)) {
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@@ -85,6 +119,10 @@ const multi = {
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Keltner: { make: () => new wickra.Keltner(20, 10, 2), fields: ['upper', 'middle', 'lower'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
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Donchian: { make: () => new wickra.Donchian(20), fields: ['upper', 'middle', 'lower'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
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Aroon: { make: () => new wickra.Aroon(14), fields: ['up', 'down'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
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Vortex: { make: () => new wickra.Vortex(14), fields: ['plus', 'minus'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
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SuperTrend: { make: () => new wickra.SuperTrend(10, 3), fields: ['value', 'direction'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
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ChandelierExit: { make: () => new wickra.ChandelierExit(22, 3), fields: ['longStop', 'shortStop'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
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ChandeKrollStop: { make: () => new wickra.ChandeKrollStop(10, 1, 9), fields: ['stopLong', 'stopShort'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
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};
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for (const [name, d] of Object.entries(multi)) {
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@@ -163,3 +201,34 @@ test('MACD histogram equals macd minus signal', () => {
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assert.ok(v);
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assert.ok(Math.abs(v.histogram - (v.macd - v.signal)) < 1e-9);
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});
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test('TypicalPrice reference value', () => {
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// (high + low + close) / 3 = (12 + 6 + 9) / 3 = 9.
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assert.equal(new wickra.TypicalPrice().update(12, 6, 9), 9);
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});
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test('ChaikinMoneyFlow(2) reference value equals 0.5', () => {
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// Bar 1 closes at the high (MFV +100); bar 2 closes mid-range (MFV 0).
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const cmf = new wickra.ChaikinMoneyFlow(2);
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assert.equal(cmf.update(10, 8, 10, 100), null);
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assert.ok(Math.abs(cmf.update(12, 8, 10, 100) - 0.5) < 1e-9);
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});
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test('LinearRegression(3) reference values', () => {
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// Least-squares line through [1, 2, 9] is y = 4x; endpoint 4·2 = 8.
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const out = new wickra.LinearRegression(3).batch([1, 2, 9]);
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assert.ok(Number.isNaN(out[0]) && Number.isNaN(out[1]));
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assert.ok(Math.abs(out[2] - 8) < 1e-9);
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});
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test('SuperTrend flat market holds the lower band and an uptrend', () => {
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// Flat candles: ATR 2, hl2 10, lower band 10 - 3·2 = 4.
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const n = 20;
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const out = new wickra.SuperTrend(5, 3).batch(
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Array(n).fill(11),
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Array(n).fill(9),
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Array(n).fill(10),
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);
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assert.ok(Math.abs(out[2 * n - 2] - 4) < 1e-9); // value
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assert.equal(out[2 * n - 1], 1); // direction
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});
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