kingchenc
cb6da4d737
* feat(data-layer): Resampler (candle resampling) in all 10 languages Second data-layer feature (F3): resample candles into a higher timeframe. - Native (Node.js/WASM): new Resampler(timeframe) -> update(o,h,l,c,v,ts): Candle|null + flush(): Candle|null. Python the same -> tuple|None. - C ABI: wickra_resampler_new/update/flush/free (update has the multi-output shape so the generators auto-emit it; flush is bespoke). Go Update -> (Candle, bool) + Flush; C# Candle? Update/Flush; Java Candle update/flush; R update() generic + a flush() S3 method (extends base::flush); C/C++ direct. - Cross-language golden (testdata/golden/data_resampled.csv): the shared input candles resampled into 5-unit buckets, the final partial bucket via flush, pinned bit-for-bit across every binding. Verified locally in all 10 (3 candles for the 5-unit smoke; 16 for the golden). The WickraCandle output record is shared with the tick aggregator (deduped). * test(node): exclude data-layer types from the indicator completeness contract The Resampler exposes update(), so the completeness test flagged it as an indicator and required batch/reset/isReady/warmupPeriod, which a data-layer type does not have. Exclude TickAggregator and Resampler like the bar builders.
74 lines
2.3 KiB
JavaScript
74 lines
2.3 KiB
JavaScript
// Cross-language data-layer parity for the WASM binding: replay the shared
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// golden tick stream through TickAggregator and check the candles against the
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// Rust-generated fixtures, with and without gap filling.
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const test = require('node:test');
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const assert = require('node:assert/strict');
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const fs = require('node:fs');
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const path = require('node:path');
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const W = require('../pkg/wickra_wasm.js');
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const GOLDEN = path.resolve(__dirname, '..', '..', '..', 'testdata', 'golden');
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function readCsv(name) {
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const lines = fs.readFileSync(path.join(GOLDEN, `${name}.csv`), 'utf8').split(/\r?\n/);
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lines.shift();
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return lines.filter((l) => l.length > 0).map((l) => l.split(',').map(Number));
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}
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const TICKS = readCsv('data_ticks');
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function run(gapFill) {
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const agg = new W.TickAggregator(1000, gapFill);
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const out = [];
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for (const [price, size, ts] of TICKS) {
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for (const c of agg.push(price, size, ts)) {
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out.push([c.open, c.high, c.low, c.close, c.volume, c.timestamp]);
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}
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}
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return out;
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}
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function assertCandles(got, want, label) {
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assert.equal(got.length, want.length, `${label}: candle count ${got.length} vs ${want.length}`);
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for (let i = 0; i < got.length; i++) {
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for (let j = 0; j < 6; j++) {
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const tol = 1e-9 * Math.max(1, Math.abs(want[i][j]));
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assert.ok(
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Math.abs(got[i][j] - want[i][j]) <= tol,
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`${label} row ${i} col ${j}: ${got[i][j]} vs ${want[i][j]}`,
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);
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}
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}
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}
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test('wasm tick aggregator matches the golden candles', () => {
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assertCandles(run(false), readCsv('data_candles'), 'no-gap');
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});
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test('wasm tick aggregator gap-fill matches the golden candles', () => {
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assertCandles(run(true), readCsv('data_candles_gap'), 'gap');
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});
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const INPUT = readCsv('input'); // open,high,low,close,volume (timestamp = row index)
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function runResample() {
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const r = new W.Resampler(5);
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const out = [];
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INPUT.forEach(([o, h, l, c, v], i) => {
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const candle = r.update(o, h, l, c, v, i);
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if (candle) {
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out.push([candle.open, candle.high, candle.low, candle.close, candle.volume, candle.timestamp]);
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}
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});
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const f = r.flush();
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if (f) {
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out.push([f.open, f.high, f.low, f.close, f.volume, f.timestamp]);
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}
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return out;
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}
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test('wasm resampler matches the golden candles', () => {
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assertCandles(runResample(), readCsv('data_resampled'), 'resample');
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});
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