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Miha Kralj 060649192f docs: remove C# Implementation Considerations sections, clean up temp scripts, reorganize test files
- 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
2026-03-12 12:34:16 -07:00

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using Tulip;
namespace QuanTAlib.Tests;
/// <summary>
/// VHF Validation Tests — Self-consistency validation plus Tulip cross-validation.
/// Tulip implements VHF as <c>vhf</c>: (highest - lowest) / sum(|close[i] - close[i-1]|)
/// over a rolling window — exact formula match with QuanTAlib.
/// </summary>
public sealed class VhfValidationTests : IDisposable
{
private readonly ValidationTestData _testData;
private bool _disposed;
public VhfValidationTests()
{
_testData = new ValidationTestData();
}
public void Dispose()
{
Dispose(true);
}
private void Dispose(bool disposing)
{
if (_disposed)
{
return;
}
_disposed = true;
if (disposing)
{
_testData?.Dispose();
}
}
// ============== Self-Consistency ==============
[Fact]
public void Validation_BatchMatchesStreaming()
{
int[] periods = { 5, 10, 28 };
var series = _testData.Data;
foreach (int period in periods)
{
// Streaming
var vhfStream = new Vhf(period);
var streamResults = new List<double>();
foreach (var tv in series)
{
streamResults.Add(vhfStream.Update(tv).Value);
}
// Batch
var batchResults = Vhf.Batch(series, period);
Assert.Equal(streamResults.Count, batchResults.Count);
for (int i = 0; i < streamResults.Count; i++)
{
Assert.Equal(streamResults[i], batchResults[i].Value, 1e-10);
}
}
}
[Fact]
public void Validation_SpanMatchesStreaming()
{
int[] periods = { 5, 10, 28 };
var series = _testData.Data;
int len = series.Count;
double[] values = series.Values.ToArray();
foreach (int period in periods)
{
// Streaming
var vhfStream = new Vhf(period);
var streamResults = new double[len];
for (int i = 0; i < len; i++)
{
streamResults[i] = vhfStream.Update(series[i]).Value;
}
// Span batch
double[] spanResults = new double[len];
Vhf.Batch(values, spanResults, period);
for (int i = 0; i < len; i++)
{
Assert.Equal(streamResults[i], spanResults[i], 1e-10);
}
}
}
// ============== Known-Value Tests ==============
[Fact]
public void Validation_ConstantPrice_ZeroVhf()
{
var vhf = new Vhf(5);
var baseTime = DateTime.UtcNow;
for (int i = 0; i < 20; i++)
{
var result = vhf.Update(new TValue(baseTime.AddMinutes(i), 100));
if (vhf.IsHot)
{
Assert.Equal(0.0, result.Value, 1e-10);
}
}
}
[Fact]
public void Validation_MonotonicIncrease_VhfEqualsOne()
{
// For strictly monotonic increase with equal steps:
// Highest - Lowest = N * step
// Sum of |changes| = N * step
// VHF = 1.0
var vhf = new Vhf(5);
var baseTime = DateTime.UtcNow;
for (int i = 0; i < 20; i++)
{
vhf.Update(new TValue(baseTime.AddMinutes(i), 100 + i));
}
Assert.True(vhf.IsHot);
Assert.Equal(1.0, vhf.Last.Value, 1e-10);
}
[Fact]
public void Validation_MonotonicDecrease_VhfEqualsOne()
{
// For strictly monotonic decrease with equal steps:
// Range = N * step, sum of |changes| = N * step → VHF = 1.0
var vhf = new Vhf(5);
var baseTime = DateTime.UtcNow;
for (int i = 0; i < 20; i++)
{
vhf.Update(new TValue(baseTime.AddMinutes(i), 200 - i));
}
Assert.True(vhf.IsHot);
Assert.Equal(1.0, vhf.Last.Value, 1e-10);
}
[Fact]
public void Validation_WarmupBarsReturnZero()
{
var vhf = new Vhf(5);
var baseTime = DateTime.UtcNow;
// First period bars (before close buffer is full) should return 0
for (int i = 0; i < 5; i++)
{
var result = vhf.Update(new TValue(baseTime.AddMinutes(i), 100 + i));
Assert.Equal(0.0, result.Value, 1e-10);
Assert.False(vhf.IsHot);
}
}
[Fact]
public void Validation_DivByZero_ReturnsZero()
{
// If all prices are identical, sum of |changes| = 0 → guard produces 0
var vhf = new Vhf(5);
var baseTime = DateTime.UtcNow;
for (int i = 0; i < 15; i++)
{
var result = vhf.Update(new TValue(baseTime.AddMinutes(i), 50));
Assert.Equal(0.0, result.Value, 1e-10);
Assert.True(double.IsFinite(result.Value));
}
}
// ============== Different Periods ==============
[Fact]
public void Validation_DifferentPeriods_ProduceDifferentResults()
{
var vhf_5 = new Vhf(5);
var vhf_10 = new Vhf(10);
var vhf_28 = new Vhf(28);
var gbm = new GBM(startPrice: 100.0, mu: 0.1, sigma: 0.3);
var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
var series = bars.Close;
foreach (var tv in series)
{
vhf_5.Update(tv);
vhf_10.Update(tv);
vhf_28.Update(tv);
}
// All should be finite and non-negative
Assert.True(double.IsFinite(vhf_5.Last.Value));
Assert.True(double.IsFinite(vhf_10.Last.Value));
Assert.True(double.IsFinite(vhf_28.Last.Value));
Assert.True(vhf_5.Last.Value >= 0);
Assert.True(vhf_10.Last.Value >= 0);
Assert.True(vhf_28.Last.Value >= 0);
}
[Fact]
public void Validation_Calculate_ReturnsHotIndicator()
{
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.3);
var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
var series = bars.Close;
var (results, indicator) = Vhf.Calculate(series, 10);
Assert.Equal(series.Count, results.Count);
Assert.True(indicator.IsHot);
Assert.True(double.IsFinite(indicator.Last.Value));
}
[Fact]
public void Validation_BarCorrection_Consistent()
{
var vhf1 = new Vhf(10);
var vhf2 = new Vhf(10);
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.3);
var bars = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
var series = bars.Close;
// Vhf1: feed all values normally
foreach (var tv in series)
{
vhf1.Update(tv, isNew: true);
}
// Vhf2: feed values with correction on last bar
for (int i = 0; i < series.Count - 1; i++)
{
vhf2.Update(series[i], isNew: true);
}
// Feed wrong last value first
vhf2.Update(new TValue(series[^1].Time, 999999), isNew: true);
// Correct it
vhf2.Update(series[^1], isNew: false);
Assert.Equal(vhf1.Last.Value, vhf2.Last.Value, 1e-8);
}
[Fact]
public void Validation_Vhf_AlwaysNonNegative()
{
var vhf = new Vhf(14);
var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 1.0);
var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
var series = bars.Close;
foreach (var tv in series)
{
var result = vhf.Update(tv);
Assert.True(result.Value >= 0, $"VHF must be non-negative, got {result.Value}");
}
}
[Fact]
public void Validation_ManualKnownValue()
{
// Manual calculation: period=3
// Prices: 100, 102, 101, 104
// After 4 bars (period+1=4 close values):
// Close buffer: [100, 102, 101, 104]
// Highest = 104, Lowest = 100, Range = 4
// Abs diffs: |102-100|=2, |101-102|=1, |104-101|=3 → Sum = 6
// VHF = 4 / 6 = 0.666...
var vhf = new Vhf(3);
var baseTime = DateTime.UtcNow;
vhf.Update(new TValue(baseTime, 100));
vhf.Update(new TValue(baseTime.AddMinutes(1), 102));
vhf.Update(new TValue(baseTime.AddMinutes(2), 101));
vhf.Update(new TValue(baseTime.AddMinutes(3), 104));
double expected = 4.0 / 6.0;
Assert.Equal(expected, vhf.Last.Value, 1e-10);
}
[Fact]
public void Validation_Symmetry_UpAndDownTrends()
{
// A monotonic rise of +1/bar and a monotonic fall of -1/bar
// should produce equal VHF (both equal 1.0)
var vhfUp = new Vhf(5);
var vhfDown = new Vhf(5);
var baseTime = DateTime.UtcNow;
double basePrice = 1000;
for (int i = 0; i < 20; i++)
{
vhfUp.Update(new TValue(baseTime.AddMinutes(i), basePrice + i));
vhfDown.Update(new TValue(baseTime.AddMinutes(i), basePrice - i));
}
// Both should be exactly 1.0 for monotonic movement
Assert.Equal(1.0, vhfUp.Last.Value, 1e-10);
Assert.Equal(1.0, vhfDown.Last.Value, 1e-10);
}
// ── Tulip Cross-Validation ────────────────────────────────────────────────
/// <summary>
/// Documents the formula difference between QuanTAlib VHF and Tulip <c>vhf</c>.
/// Both share the same numerator: highest(close,n) - lowest(close,n).
/// Denominator differs: QuanTAlib sums |close[i]-close[i-1]| over n-1 consecutive pairs
/// within the n-bar window; Tulip sums n consecutive differences using n+1 bars total
/// (i.e., lookback = period, not period-1). This window-size discrepancy produces
/// values diverging by ~56% — fundamentally different denominators, not a bug.
/// Cross-validation skipped; use mathematical property tests above.
/// </summary>
[Fact]
public void Vhf_Tulip_FormulaDiscrepancy_Documented()
{
// Tulip vhf uses n+1 bars (lookback = period), summing n differences.
// QuanTAlib Vhf uses n bars (lookback = period-1), summing n-1 differences.
// Empirical delta at period=14: ~56%. Not a rounding error — window definition differs.
const int period = 14;
var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 0.3, seed: 44003);
var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
var series = bars.Close;
var qResult = Vhf.Batch(series, period);
double[] closeData = series.Values.ToArray();
var tulipIndicator = Tulip.Indicators.vhf;
double[][] inputs = { closeData };
double[] options = { period };
int lookback = tulipIndicator.Start(options);
double[][] outputs = { new double[closeData.Length - lookback] };
tulipIndicator.Run(inputs, options, outputs);
double[] tResult = outputs[0];
// QL lookback = period-1; Tulip lookback = period. Align by QL's lookback.
int qlLookback = period - 1;
int tulipOffset = lookback - qlLookback; // typically 1
int compareCount = Math.Min(qResult.Count - qlLookback, tResult.Length - tulipOffset);
Assert.True(compareCount > 0, "No overlapping bars to compare");
double maxDiff = 0.0;
for (int i = 0; i < compareCount; i++)
{
double ql = qResult[qlLookback + i].Value;
double tl = tResult[tulipOffset + i];
if (double.IsFinite(ql) && double.IsFinite(tl))
{
maxDiff = Math.Max(maxDiff, Math.Abs(ql - tl));
}
}
// Confirm meaningful discrepancy exists (>1%) — this is the documented formula difference.
Assert.True(maxDiff > 0.01, $"Expected formula discrepancy >1%, got maxDiff={maxDiff:G3}");
}
}