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.

bindings/csharp/Wickra.Tests/DataLayerTests.cs

@@ -28,6 +28,37 @@ public class DataLayerTests
         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")]