Files
wickra/bindings/csharp/Wickra.Tests/DataLayerTests.cs
T
kingchenc cb6da4d737 feat(data-layer): Resampler (candle resampling) in all 10 languages (#310)
* 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.
2026-06-15 22:36:16 +02:00

91 lines
3.2 KiB
C#

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