Files
Miha Kralj 67ad6f0cba v0.8.7: Replace periodic ResyncInterval with Kahan compensated summation
Comprehensive refactor across all indicators replacing the periodic
ResyncInterval-based drift correction (every 1000 ticks recalculate
from scratch) with Kahan compensated summation for running sums.

Key changes:
- Remove ResyncInterval constants and TickCount fields from all State records
- Add Kahan compensation fields (SumComp, SumSqComp, etc.) to State records
- Replace naive sum += val - removed with Kahan delta pattern
- Remove Resync()/RecalculateSum() methods that did O(N) recalculation
- Update batch/SIMD paths to use Kahan compensation instead of resync loops
- IIR filters (EMA, REMA, RGMA) simplified: inherently self-correcting
- Version bump to 0.8.7
- Build system: README version stamping via Directory.Build.props
- Minor doc/test tolerance adjustments for new numerical characteristics

Affected modules: channels, core, cycles, dynamics, errors, momentum,
oscillators, statistics, trends_FIR, trends_IIR, volatility, volume
2026-03-13 22:01:31 -07:00

451 lines
13 KiB
C#

using Xunit;
namespace QuanTAlib.Tests;
public sealed class CtiTests
{
private const int DefaultPeriod = 20;
private const double Tolerance = 1e-7;
// ───── A) Constructor validation ─────
[Fact]
public void Constructor_PeriodOne_ThrowsArgumentException()
{
var ex = Assert.Throws<ArgumentException>(() => new Cti(period: 1));
Assert.Equal("period", ex.ParamName);
}
[Fact]
public void Constructor_PeriodZero_ThrowsArgumentException()
{
var ex = Assert.Throws<ArgumentException>(() => new Cti(period: 0));
Assert.Equal("period", ex.ParamName);
}
[Fact]
public void Constructor_NegativePeriod_ThrowsArgumentException()
{
var ex = Assert.Throws<ArgumentException>(() => new Cti(period: -5));
Assert.Equal("period", ex.ParamName);
}
[Fact]
public void Constructor_ValidPeriod_SetsProperties()
{
var cti = new Cti(period: 10);
Assert.Equal(10, cti.Period);
Assert.Equal("Cti(10)", cti.Name);
Assert.Equal(10, cti.WarmupPeriod);
}
// ───── B) Basic calculation ─────
[Fact]
public void Update_ReturnsTValue()
{
var cti = new Cti(DefaultPeriod);
var result = cti.Update(new TValue(DateTime.UtcNow, 100.0));
Assert.IsType<TValue>(result);
}
[Fact]
public void Update_Last_IsAccessible()
{
var cti = new Cti(DefaultPeriod);
cti.Update(new TValue(DateTime.UtcNow, 100.0));
Assert.NotEqual(default, cti.Last);
Assert.False(cti.IsHot);
Assert.Equal($"Cti({DefaultPeriod})", cti.Name);
}
[Fact]
public void Update_OutputBounded_MinusOneToOne()
{
var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 0.3, seed: 42);
var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
var cti = new Cti(DefaultPeriod);
foreach (var bar in bars.Close)
{
cti.Update(bar);
if (cti.IsHot)
{
Assert.InRange(cti.Last.Value, -1.0, 1.0);
}
}
}
[Fact]
public void Update_PerfectAscending_CTI_Equals_One()
{
// Perfect arithmetic sequence → perfect positive linear correlation → CTI = 1.0
var cti = new Cti(period: 10);
for (int i = 1; i <= 15; i++)
{
cti.Update(new TValue(DateTime.UtcNow, i * 1.0));
}
Assert.True(cti.IsHot);
Assert.Equal(1.0, cti.Last.Value, 10);
}
[Fact]
public void Update_PerfectDescending_CTI_Equals_MinusOne()
{
// Perfect descending sequence → CTI = -1.0
var cti = new Cti(period: 10);
for (int i = 15; i >= 1; i--)
{
cti.Update(new TValue(DateTime.UtcNow, i * 1.0));
}
Assert.True(cti.IsHot);
Assert.Equal(-1.0, cti.Last.Value, 10);
}
[Fact]
public void Update_ConstantInput_CTI_IsNotNaN()
{
// Constant price → denomY = 0 → ComputePearson returns 0.0, not NaN
var cti = new Cti(period: 5);
for (int i = 0; i < 10; i++)
{
cti.Update(new TValue(DateTime.UtcNow, 50.0));
}
Assert.True(double.IsFinite(cti.Last.Value));
Assert.Equal(0.0, cti.Last.Value, Tolerance);
}
// ───── C) State + bar correction ─────
[Fact]
public void Update_IsNew_True_AdvancesState()
{
var cti = new Cti(DefaultPeriod);
cti.Update(new TValue(DateTime.UtcNow, 100.0), isNew: true);
cti.Update(new TValue(DateTime.UtcNow, 110.0), isNew: true);
Assert.NotEqual(default, cti.Last);
}
[Fact]
public void Update_IsNew_False_RollsBack()
{
var cti = new Cti(period: 5);
for (int i = 0; i < 6; i++)
{
cti.Update(new TValue(DateTime.UtcNow, 100.0 + i), isNew: true);
}
// Bar correction: rewrite last bar
cti.Update(new TValue(DateTime.UtcNow, 105.0), isNew: false);
var corrected = cti.Last;
// Same correction again → same result
cti.Update(new TValue(DateTime.UtcNow, 105.0), isNew: false);
var corrected2 = cti.Last;
Assert.Equal(corrected.Value, corrected2.Value, Tolerance);
}
[Fact]
public void Update_IterativeCorrections_Restore()
{
var cti = new Cti(period: 5);
double[] data = [100, 102, 104, 106, 108, 110];
for (int i = 0; i < data.Length; i++)
{
cti.Update(new TValue(DateTime.UtcNow, data[i]), isNew: true);
}
var baseline = cti.Last.Value;
// Apply three corrections, then restore original value
cti.Update(new TValue(DateTime.UtcNow, 999.0), isNew: false);
cti.Update(new TValue(DateTime.UtcNow, 888.0), isNew: false);
cti.Update(new TValue(DateTime.UtcNow, data[^1]), isNew: false);
Assert.Equal(baseline, cti.Last.Value, Tolerance);
}
[Fact]
public void Reset_ClearsState()
{
var cti = new Cti(DefaultPeriod);
for (int i = 0; i < 25; i++)
{
cti.Update(new TValue(DateTime.UtcNow, 100.0 + i));
}
Assert.True(cti.IsHot);
cti.Reset();
Assert.False(cti.IsHot);
Assert.Equal(default, cti.Last);
}
// ───── D) Warmup/convergence ─────
[Fact]
public void IsHot_FlipsAfterPeriodBars()
{
var cti = new Cti(period: 5);
for (int i = 0; i < 4; i++)
{
cti.Update(new TValue(DateTime.UtcNow, 100.0 + i));
Assert.False(cti.IsHot);
}
cti.Update(new TValue(DateTime.UtcNow, 104.0));
Assert.True(cti.IsHot);
}
[Fact]
public void WarmupPeriod_MatchesPeriod()
{
var cti = new Cti(period: 20);
Assert.Equal(20, cti.WarmupPeriod);
}
// ───── E) Robustness ─────
[Fact]
public void Update_NaN_UsesLastValid()
{
var cti = new Cti(period: 5);
for (int i = 0; i < 6; i++)
{
cti.Update(new TValue(DateTime.UtcNow, 100.0 + i));
}
_ = cti.Last.Value;
cti.Update(new TValue(DateTime.UtcNow, double.NaN));
Assert.True(double.IsFinite(cti.Last.Value));
}
[Fact]
public void Update_Infinity_UsesLastValid()
{
var cti = new Cti(period: 5);
for (int i = 0; i < 6; i++)
{
cti.Update(new TValue(DateTime.UtcNow, 100.0 + i));
}
cti.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
Assert.True(double.IsFinite(cti.Last.Value));
cti.Update(new TValue(DateTime.UtcNow, double.NegativeInfinity));
Assert.True(double.IsFinite(cti.Last.Value));
}
[Fact]
public void Update_BatchNaN_Safe()
{
var cti = new Cti(period: 5);
for (int i = 0; i < 3; i++)
{
cti.Update(new TValue(DateTime.UtcNow, double.NaN));
}
Assert.True(double.IsFinite(cti.Last.Value));
}
// ───── F) Consistency (4 modes match) ─────
[Fact]
public void AllModes_ProduceSameResults()
{
int period = 10;
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
TSeries source = bars.Close;
// 1. Streaming
var streaming = new Cti(period);
var streamResults = new double[source.Count];
for (int i = 0; i < source.Count; i++)
{
streamResults[i] = streaming.Update(source[i]).Value;
}
// 2. Batch TSeries
TSeries batchSeries = Cti.Batch(source, period);
// 3. Batch Span
var spanOutput = new double[source.Count];
Cti.Batch(source.Values, spanOutput, period);
// 4. Event-based
var eventSource = new TSeries();
var eventIndicator = new Cti(eventSource, period);
var eventResults = new double[source.Count];
for (int i = 0; i < source.Count; i++)
{
eventSource.Add(source[i]);
eventResults[i] = eventIndicator.Last.Value;
}
for (int i = period; i < source.Count; i++)
{
Assert.Equal(streamResults[i], batchSeries.Values[i], Tolerance);
Assert.Equal(streamResults[i], spanOutput[i], Tolerance);
Assert.Equal(streamResults[i], eventResults[i], Tolerance);
}
}
// ───── G) Span API tests ─────
[Fact]
public void Batch_Span_MismatchedLength_ThrowsArgumentException()
{
var source = new double[10];
var output = new double[5];
var ex = Assert.Throws<ArgumentException>(() => Cti.Batch(source.AsSpan(), output.AsSpan(), DefaultPeriod));
Assert.Equal("output", ex.ParamName);
}
[Fact]
public void Batch_Span_PeriodOne_ThrowsArgumentException()
{
var source = new double[10];
var output = new double[10];
var ex = Assert.Throws<ArgumentException>(() => Cti.Batch(source.AsSpan(), output.AsSpan(), 1));
Assert.Equal("period", ex.ParamName);
}
[Fact]
public void Batch_Span_Empty_NoException()
{
double[] source = [];
double[] output = [];
var ex = Record.Exception(() => Cti.Batch(source.AsSpan(), output.AsSpan(), DefaultPeriod));
Assert.Null(ex);
}
[Fact]
public void Batch_Span_MatchesTSeries()
{
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 7);
var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
TSeries source = bars.Close;
int period = 10;
TSeries batchTs = Cti.Batch(source, period);
var spanOutput = new double[source.Count];
Cti.Batch(source.Values, spanOutput, period);
for (int i = 0; i < source.Count; i++)
{
Assert.Equal(batchTs.Values[i], spanOutput[i], Tolerance);
}
}
[Fact]
public void Batch_Span_NaN_Handled()
{
double[] src = [1, 2, double.NaN, 4, 5, 6, 7, 8, 9, 10];
var output = new double[src.Length];
var ex = Record.Exception(() => Cti.Batch(src.AsSpan(), output.AsSpan(), 5));
Assert.Null(ex);
Assert.True(output.All(double.IsFinite));
}
[Fact]
public void Batch_Span_PerfectAscending_OutputsOne()
{
int period = 5;
double[] src = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
var output = new double[src.Length];
Cti.Batch(src.AsSpan(), output.AsSpan(), period);
// After warmup, all values should be 1.0
for (int i = period - 1; i < src.Length; i++)
{
Assert.Equal(1.0, output[i], 10);
}
}
[Fact]
public void Batch_Span_LargeDataset_NoStackOverflow()
{
double[] src = new double[10000];
double[] output = new double[10000];
for (int i = 0; i < src.Length; i++)
{
src[i] = 100.0 + i * 0.01;
}
var ex = Record.Exception(() => Cti.Batch(src.AsSpan(), output.AsSpan(), DefaultPeriod));
Assert.Null(ex);
}
// ───── H) Chainability ─────
[Fact]
public void PubEvent_FiresOnUpdate()
{
var cti = new Cti(DefaultPeriod);
int firedCount = 0;
cti.Pub += (object? _, in TValueEventArgs _) => firedCount++;
cti.Update(new TValue(DateTime.UtcNow, 100.0));
Assert.Equal(1, firedCount);
}
[Fact]
public void EventChaining_Works()
{
var source = new TSeries();
var cti = new Cti(source, period: 5);
var downstream = new TSeries();
cti.Pub += (object? _, in TValueEventArgs e) => downstream.Add(e.Value);
for (int i = 0; i < 10; i++)
{
source.Add(new TValue(DateTime.UtcNow, 100.0 + i));
}
Assert.Equal(10, downstream.Count);
}
// ───── Calculate ─────
[Fact]
public void Calculate_ReturnsResultsAndHotIndicator()
{
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
var bars = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
TSeries source = bars.Close;
var (results, indicator) = Cti.Calculate(source, period: 5);
Assert.Equal(source.Count, results.Count);
Assert.True(indicator.IsHot);
}
// ───── Update(TSeries) ─────
[Fact]
public void UpdateTSeries_MatchesStreaming()
{
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
TSeries source = bars.Close;
int period = 10;
var streaming = new Cti(period);
var streamResults = new double[source.Count];
for (int i = 0; i < source.Count; i++)
{
streamResults[i] = streaming.Update(source[i]).Value;
}
var batch = new Cti(period);
TSeries batchResults = batch.Update(source);
for (int i = period; i < source.Count; i++)
{
Assert.Equal(streamResults[i], batchResults.Values[i], Tolerance);
}
}
}