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.
91 lines
3.2 KiB
C#
91 lines
3.2 KiB
C#
using System;
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using System.Collections.Generic;
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using System.Globalization;
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using System.IO;
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using Wickra;
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using Xunit;
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// Cross-language data-layer parity: replay the shared golden tick stream through
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// the TickAggregator and check the candles against the Rust reference, with and
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// without gap filling.
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public class DataLayerTests
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{
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private static string GoldenDir([System.Runtime.CompilerServices.CallerFilePath] string file = "") =>
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Path.GetFullPath(Path.Combine(Path.GetDirectoryName(file)!, "..", "..", "..", "testdata", "golden"));
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private static double[][] Read(string name)
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{
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var lines = File.ReadAllLines(Path.Combine(GoldenDir(), name + ".csv"));
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var rows = new List<double[]>();
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for (var i = 1; i < lines.Length; i++)
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{
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if (lines[i].Length == 0)
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{
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continue;
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}
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rows.Add(Array.ConvertAll(lines[i].Split(','), s => double.Parse(s, CultureInfo.InvariantCulture)));
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}
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return rows.ToArray();
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}
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[Fact]
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public void ResamplerMatchesGolden()
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{
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var input = Read("input"); // open,high,low,close,volume (timestamp = row index)
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using var r = new Resampler(5);
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var got = new List<double[]>();
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for (var i = 0; i < input.Length; i++)
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{
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var c = r.Update(input[i][0], input[i][1], input[i][2], input[i][3], input[i][4], i);
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if (c.HasValue)
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{
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got.Add(new[] { c.Value.Open, c.Value.High, c.Value.Low, c.Value.Close, c.Value.Volume, (double)c.Value.Timestamp });
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}
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}
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var f = r.Flush();
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if (f.HasValue)
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{
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got.Add(new[] { f.Value.Open, f.Value.High, f.Value.Low, f.Value.Close, f.Value.Volume, (double)f.Value.Timestamp });
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}
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var want = Read("data_resampled");
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Assert.Equal(want.Length, got.Count);
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for (var i = 0; i < got.Count; i++)
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{
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for (var j = 0; j < 6; j++)
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{
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var tol = 1e-9 * Math.Max(1, Math.Abs(want[i][j]));
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Assert.True(Math.Abs(got[i][j] - want[i][j]) <= tol, $"resample 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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[Theory]
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[InlineData(false, "data_candles")]
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[InlineData(true, "data_candles_gap")]
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public void TickAggregatorMatchesGolden(bool gapFill, string fixture)
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{
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var ticks = Read("data_ticks");
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using var agg = new TickAggregator(1000, gapFill);
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var got = new List<double[]>();
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foreach (var t in ticks)
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{
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foreach (var c in agg.Push(t[0], t[1], (long)t[2]))
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{
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got.Add(new[] { c.Open, c.High, c.Low, c.Close, c.Volume, (double)c.Timestamp });
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}
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}
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var want = Read(fixture);
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Assert.Equal(want.Length, got.Count);
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for (var i = 0; i < got.Count; i++)
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{
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for (var j = 0; j < 6; j++)
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{
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var tol = 1e-9 * Math.Max(1, Math.Abs(want[i][j]));
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Assert.True(
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Math.Abs(got[i][j] - want[i][j]) <= tol,
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$"{fixture} 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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