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060649192f
- Remove 'C# Implementation Considerations' sections from 34 indicator .md files - Delete 29 temp PowerShell scripts (_fix_mojibake.ps1, _hex_scan.ps1, etc.) - Move test files into tests/ subdirectories for consistent project structure - Add trader-focused bullet points to indicator documentation
137 lines
3.8 KiB
C#
137 lines
3.8 KiB
C#
namespace QuanTAlib.Tests;
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/// <summary>
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/// Trim self-consistency validation.
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/// No external library has a built-in trimmed mean moving average,
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/// so we validate internal consistency: batch == streaming == span.
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/// </summary>
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public class TrimValidationTests
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{
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private const double Tolerance = 1e-10;
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[Fact]
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public void Trim_Streaming_Equals_SpanBatch()
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{
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var rng = new GBM(startPrice: 100, mu: 0.0001, sigma: 0.015, seed: 1001);
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int n = 200;
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int period = 20;
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double trimPct = 10.0;
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var prices = new double[n];
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var times = new long[n];
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var t0 = DateTime.UtcNow;
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for (int i = 0; i < n; i++)
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{
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TBar bar = rng.Next();
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prices[i] = bar.Close;
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times[i] = t0.AddMinutes(i).Ticks;
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}
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// Streaming
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var streaming = new Trim(period, trimPct);
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var streamValues = new double[n];
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for (int i = 0; i < n; i++)
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{
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streamValues[i] = streaming.Update(new TValue(new DateTime(times[i], DateTimeKind.Utc), prices[i])).Value;
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}
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// Span batch
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var spanValues = new double[n];
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Trim.Batch(prices, spanValues, period, trimPct);
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for (int i = period - 1; i < n; i++)
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{
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Assert.Equal(streamValues[i], spanValues[i], 9);
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}
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}
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[Fact]
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public void Trim_TrimPctZero_EqualsSMA_LongSeries()
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{
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var rng = new GBM(startPrice: 100, mu: 0.0001, sigma: 0.015, seed: 2002);
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int n = 200;
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int period = 14;
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var prices = new double[n];
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var times = new long[n];
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var t0 = DateTime.UtcNow;
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for (int i = 0; i < n; i++)
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{
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TBar bar = rng.Next();
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prices[i] = bar.Close;
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times[i] = t0.AddMinutes(i).Ticks;
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}
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var smaRef = new double[n];
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var trimOut = new double[n];
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// Manual SMA using span for reference (trimZero is redundant — Batch is the span path)
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Trim.Batch(prices, trimOut, period, 0.0);
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// Manual reference: SMA with period
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for (int i = 0; i < n; i++)
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{
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int start = Math.Max(0, i - period + 1);
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double sum = 0;
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int cnt = 0;
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for (int j = start; j <= i; j++)
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{
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sum += prices[j];
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cnt++;
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}
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smaRef[i] = sum / cnt;
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}
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// After warmup, both should match
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for (int i = period - 1; i < n; i++)
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{
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Assert.Equal(smaRef[i], trimOut[i], 9);
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}
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}
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[Fact]
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public void Trim_BatchTSeries_EqualsStreaming()
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{
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var rng = new GBM(startPrice: 100, mu: 0.0001, sigma: 0.015, seed: 3003);
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int n = 50;
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int period = 10;
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double trimPct = 15.0;
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var series = new TSeries();
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var t0 = DateTime.UtcNow;
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for (int i = 0; i < n; i++)
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{
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TBar bar = rng.Next();
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series.Add(new TValue(t0.AddMinutes(i), bar.Close));
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}
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var batchResult = Trim.Batch(series, period, trimPct);
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var streaming = new Trim(period, trimPct);
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TValue lastStream = default;
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for (int i = 0; i < n; i++)
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{
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lastStream = streaming.Update(series[i]);
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}
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Assert.Equal(lastStream.Value, batchResult[n - 1].Value, 9);
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}
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[Fact]
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public void Trim_HighTrimPct_ApproachesMedian()
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{
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// With trimPct=49 on period=10, trimCount=4, keepCount=2 (middle 2 values)
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var trim = new Trim(10, 49.0);
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double[] vals = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
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foreach (double v in vals)
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{
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trim.Update(new TValue(DateTime.UtcNow, v));
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}
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// keepCount = 10 - 2*4 = 2, trimCount=4
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// middle 2 values of sorted [1..10] = [5,6], mean = 5.5
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Assert.Equal(5.5, trim.Last.Value, 10);
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}
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}
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