mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-07 13:37:44 +00:00
Miha Kralj
67ad6f0cba
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
703 lines
22 KiB
C#
703 lines
22 KiB
C#
namespace QuanTAlib.Tests;
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public class RemaTests
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{
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[Fact]
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public void Rema_Constructor_Period_ValidatesInput()
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{
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Assert.Throws<ArgumentOutOfRangeException>(() => new Rema(0));
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Assert.Throws<ArgumentOutOfRangeException>(() => new Rema(-1));
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var rema = new Rema(10);
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Assert.NotNull(rema);
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}
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[Fact]
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public void Rema_Constructor_Lambda_ValidatesInput()
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{
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Assert.Throws<ArgumentOutOfRangeException>(() => new Rema(10, -0.1));
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Assert.Throws<ArgumentOutOfRangeException>(() => new Rema(10, 1.1));
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var rema1 = new Rema(10, 0.0);
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var rema2 = new Rema(10, 1.0);
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var rema3 = new Rema(10, 0.5);
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Assert.NotNull(rema1);
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Assert.NotNull(rema2);
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Assert.NotNull(rema3);
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}
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[Fact]
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public void Rema_Calc_ReturnsValue()
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{
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var rema = new Rema(10);
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Assert.Equal(0, rema.Last.Value);
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TValue result = rema.Update(new TValue(DateTime.UtcNow, 100));
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Assert.True(result.Value > 0);
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Assert.Equal(result.Value, rema.Last.Value);
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}
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[Fact]
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public void Rema_Calc_IsNew_AcceptsParameter()
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{
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var rema = new Rema(10);
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rema.Update(new TValue(DateTime.UtcNow, 100), isNew: true);
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double value1 = rema.Last.Value;
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rema.Update(new TValue(DateTime.UtcNow, 105), isNew: true);
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double value2 = rema.Last.Value;
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// Values should change with new bars
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Assert.NotEqual(value1, value2);
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}
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[Fact]
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public void Rema_Calc_IsNew_False_UpdatesValue()
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{
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var rema = new Rema(10);
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rema.Update(new TValue(DateTime.UtcNow, 100));
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rema.Update(new TValue(DateTime.UtcNow, 110), isNew: true);
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double beforeUpdate = rema.Last.Value;
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rema.Update(new TValue(DateTime.UtcNow, 120), isNew: false);
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double afterUpdate = rema.Last.Value;
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// Update should change the value
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Assert.NotEqual(beforeUpdate, afterUpdate);
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}
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[Fact]
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public void Rema_Reset_ClearsState()
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{
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var rema = new Rema(10);
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rema.Update(new TValue(DateTime.UtcNow, 100));
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rema.Update(new TValue(DateTime.UtcNow, 105));
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double valueBefore = rema.Last.Value;
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rema.Reset();
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Assert.Equal(0, rema.Last.Value);
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// After reset, should accept new values
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rema.Update(new TValue(DateTime.UtcNow, 50));
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Assert.NotEqual(0, rema.Last.Value);
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Assert.NotEqual(valueBefore, rema.Last.Value);
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}
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[Fact]
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public void Rema_Properties_Accessible()
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{
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var rema = new Rema(10);
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Assert.Equal(0, rema.Last.Value);
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Assert.False(rema.IsHot);
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rema.Update(new TValue(DateTime.UtcNow, 100));
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Assert.NotEqual(0, rema.Last.Value);
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}
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[Fact]
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public void Rema_IsHot_BecomesTrueAfterWarmup()
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{
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var rema = new Rema(10);
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// Initially IsHot should be false
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Assert.False(rema.IsHot);
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int steps = 0;
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while (!rema.IsHot && steps < 1000)
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{
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rema.Update(new TValue(DateTime.UtcNow, 100));
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steps++;
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}
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Assert.True(rema.IsHot);
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Assert.True(steps > 0);
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// Similar to EMA, should become hot around 15 bars for period 10
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Assert.InRange(steps, 14, 17);
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}
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[Fact]
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public void Rema_IsHot_IsPeriodDependent()
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{
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int[] periods = [10, 20, 50];
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int[] expectedSteps = new int[periods.Length];
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for (int i = 0; i < periods.Length; i++)
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{
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int period = periods[i];
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var rema = new Rema(period);
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int steps = 0;
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while (!rema.IsHot && steps < 500)
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{
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rema.Update(new TValue(DateTime.UtcNow, 100));
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steps++;
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}
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expectedSteps[i] = steps;
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}
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// Verify warmup times increase with period
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Assert.True(expectedSteps[0] < expectedSteps[1], $"Period 10 ({expectedSteps[0]}) should be less than Period 20 ({expectedSteps[1]})");
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Assert.True(expectedSteps[1] < expectedSteps[2], $"Period 20 ({expectedSteps[1]}) should be less than Period 50 ({expectedSteps[2]})");
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}
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[Fact]
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public void Rema_Lambda1_ApproachesEma()
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{
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// With lambda=1, REMA should behave similarly to EMA
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var rema = new Rema(10, lambda: 1.0);
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var ema = new Ema(10);
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
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for (int i = 0; i < 100; i++)
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{
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var bar = gbm.Next(isNew: true);
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var input = new TValue(bar.Time, bar.Close);
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rema.Update(input);
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ema.Update(input);
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}
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// With lambda=1, REMA should be very close to EMA
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Assert.Equal(ema.Last.Value, rema.Last.Value, 1e-6);
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}
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[Fact]
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public void Rema_Lambda0_MaxRegularization()
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{
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// With lambda=0, REMA uses pure momentum continuation
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var rema0 = new Rema(10, lambda: 0.0);
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var rema05 = new Rema(10, lambda: 0.5);
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var rema1 = new Rema(10, lambda: 1.0);
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
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for (int i = 0; i < 50; i++)
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{
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var bar = gbm.Next(isNew: true);
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var input = new TValue(bar.Time, bar.Close);
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rema0.Update(input);
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rema05.Update(input);
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rema1.Update(input);
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}
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// All should produce finite values
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Assert.True(double.IsFinite(rema0.Last.Value));
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Assert.True(double.IsFinite(rema05.Last.Value));
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Assert.True(double.IsFinite(rema1.Last.Value));
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// They should generally differ (lambda affects behavior)
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// Note: exact equality is unlikely with different lambdas
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}
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[Fact]
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public void Rema_IterativeCorrections_RestoreToOriginalState()
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{
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var rema = new Rema(10);
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1);
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// Feed 10 new values
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TValue tenthInput = default;
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for (int i = 0; i < 10; i++)
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{
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var bar = gbm.Next(isNew: true);
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tenthInput = new TValue(bar.Time, bar.Close);
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rema.Update(tenthInput, isNew: true);
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}
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// Remember state after 10 values
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double remaAfterTen = rema.Last.Value;
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// Generate 9 corrections with isNew=false (different values)
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for (int i = 0; i < 9; i++)
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{
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var bar = gbm.Next(isNew: false);
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rema.Update(new TValue(bar.Time, bar.Close), isNew: false);
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}
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// Feed the remembered 10th input again with isNew=false
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TValue finalRema = rema.Update(tenthInput, isNew: false);
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// Should match the original state after 10 values
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Assert.Equal(remaAfterTen, finalRema.Value, 1e-10);
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}
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[Fact]
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public void Rema_BatchCalc_MatchesIterativeCalc()
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{
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var remaIterative = new Rema(10);
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var remaBatch = new Rema(10);
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1);
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// Generate data
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var series = new TSeries();
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for (int i = 0; i < 100; i++)
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{
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var bar = gbm.Next(isNew: true);
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series.Add(bar.Time, bar.Close);
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}
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Assert.True(series.Count > 0);
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// Calculate iteratively
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var iterativeResults = new TSeries();
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foreach (var item in series)
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{
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iterativeResults.Add(remaIterative.Update(item));
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}
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// Calculate batch
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var batchResults = remaBatch.Update(series);
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// Compare
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Assert.Equal(iterativeResults.Count, batchResults.Count);
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for (int i = 0; i < iterativeResults.Count; i++)
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{
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Assert.Equal(iterativeResults[i].Value, batchResults[i].Value, 1e-10);
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Assert.Equal(iterativeResults[i].Time, batchResults[i].Time);
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}
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}
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[Fact]
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public void Rema_NaN_Input_UsesLastValidValue()
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{
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var rema = new Rema(10);
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// Feed some valid values
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rema.Update(new TValue(DateTime.UtcNow, 100));
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rema.Update(new TValue(DateTime.UtcNow, 110));
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// Feed NaN - should use last valid value (110)
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var resultAfterNaN = rema.Update(new TValue(DateTime.UtcNow, double.NaN));
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// Result should be finite (not NaN)
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Assert.True(double.IsFinite(resultAfterNaN.Value));
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Assert.NotEqual(0, resultAfterNaN.Value);
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}
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[Fact]
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public void Rema_Infinity_Input_UsesLastValidValue()
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{
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var rema = new Rema(10);
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// Feed some valid values
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rema.Update(new TValue(DateTime.UtcNow, 100));
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rema.Update(new TValue(DateTime.UtcNow, 110));
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// Feed positive infinity - should use last valid value
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var resultAfterPosInf = rema.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
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Assert.True(double.IsFinite(resultAfterPosInf.Value));
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// Feed negative infinity - should use last valid value
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var resultAfterNegInf = rema.Update(new TValue(DateTime.UtcNow, double.NegativeInfinity));
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Assert.True(double.IsFinite(resultAfterNegInf.Value));
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}
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[Fact]
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public void Rema_MultipleNaN_ContinuesWithLastValid()
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{
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var rema = new Rema(10);
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// Feed valid values
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rema.Update(new TValue(DateTime.UtcNow, 100));
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rema.Update(new TValue(DateTime.UtcNow, 110));
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rema.Update(new TValue(DateTime.UtcNow, 120));
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// Feed multiple NaN values
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var r1 = rema.Update(new TValue(DateTime.UtcNow, double.NaN));
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var r2 = rema.Update(new TValue(DateTime.UtcNow, double.NaN));
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var r3 = rema.Update(new TValue(DateTime.UtcNow, double.NaN));
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// All results should be finite
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Assert.True(double.IsFinite(r1.Value));
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Assert.True(double.IsFinite(r2.Value));
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Assert.True(double.IsFinite(r3.Value));
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}
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[Fact]
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public void Rema_BatchCalc_HandlesNaN()
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{
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var rema = new Rema(10);
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// Create series with NaN values interspersed
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var series = new TSeries();
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series.Add(DateTime.UtcNow.Ticks, 100);
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series.Add(DateTime.UtcNow.Ticks + 1, 110);
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series.Add(DateTime.UtcNow.Ticks + 2, double.NaN);
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series.Add(DateTime.UtcNow.Ticks + 3, 120);
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series.Add(DateTime.UtcNow.Ticks + 4, double.PositiveInfinity);
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series.Add(DateTime.UtcNow.Ticks + 5, 130);
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var results = rema.Update(series);
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// All results should be finite
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foreach (var result in results)
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{
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Assert.True(double.IsFinite(result.Value), $"Expected finite value but got {result.Value}");
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}
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}
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[Fact]
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public void Rema_Reset_ClearsLastValidValue()
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{
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var rema = new Rema(10);
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// Feed values including NaN
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rema.Update(new TValue(DateTime.UtcNow, 100));
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rema.Update(new TValue(DateTime.UtcNow, double.NaN));
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// Reset
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rema.Reset();
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// After reset, first valid value should establish new baseline
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var result = rema.Update(new TValue(DateTime.UtcNow, 50));
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Assert.Equal(50.0, result.Value, 1e-10);
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}
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// ============== Span API Tests ==============
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[Fact]
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public void Rema_SpanBatch_Period_ValidatesInput()
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{
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double[] source = [1, 2, 3, 4, 5];
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double[] output = new double[5];
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double[] wrongSizeOutput = new double[3];
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// Period must be > 0
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Assert.Throws<ArgumentException>(() => Rema.Batch(source.AsSpan(), output.AsSpan(), 0));
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Assert.Throws<ArgumentException>(() => Rema.Batch(source.AsSpan(), output.AsSpan(), -1));
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// Output must be same length as source
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Assert.Throws<ArgumentException>(() => Rema.Batch(source.AsSpan(), wrongSizeOutput.AsSpan(), 3));
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}
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[Fact]
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public void Rema_SpanBatch_Lambda_ValidatesInput()
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{
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double[] source = [1, 2, 3, 4, 5];
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double[] output = new double[5];
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// Lambda must be >= 0 and <= 1
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Assert.Throws<ArgumentOutOfRangeException>(() => Rema.Batch(source.AsSpan(), output.AsSpan(), 3, -0.1));
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Assert.Throws<ArgumentOutOfRangeException>(() => Rema.Batch(source.AsSpan(), output.AsSpan(), 3, 1.1));
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}
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[Fact]
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public void Rema_SpanBatch_MatchesTSeriesBatch()
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{
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var series = new TSeries();
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double[] source = new double[100];
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double[] output = new double[100];
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
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for (int i = 0; i < 100; i++)
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{
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var bar = gbm.Next(isNew: true);
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source[i] = bar.Close;
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series.Add(bar.Time, bar.Close);
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}
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// Calculate with TSeries API
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var tseriesResult = Rema.Batch(series, 10);
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// Calculate with Span API
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Rema.Batch(source.AsSpan(), output.AsSpan(), 10);
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// Compare results
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for (int i = 0; i < 100; i++)
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{
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Assert.Equal(tseriesResult[i].Value, output[i], 1e-9);
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}
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}
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[Fact]
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public void Rema_SpanBatch_DifferentLambdas()
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{
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double[] source = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100];
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double[] output0 = new double[10];
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double[] output05 = new double[10];
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double[] output1 = new double[10];
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Rema.Batch(source.AsSpan(), output0.AsSpan(), 5, 0.0);
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Rema.Batch(source.AsSpan(), output05.AsSpan(), 5, 0.5);
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Rema.Batch(source.AsSpan(), output1.AsSpan(), 5, 1.0);
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// All should produce finite results
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for (int i = 0; i < 10; i++)
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{
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Assert.True(double.IsFinite(output0[i]));
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Assert.True(double.IsFinite(output05[i]));
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Assert.True(double.IsFinite(output1[i]));
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}
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}
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[Fact]
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public void Rema_SpanBatch_ZeroAllocation()
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{
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double[] source = new double[10000];
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double[] output = new double[10000];
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 42);
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for (int i = 0; i < source.Length; i++)
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{
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source[i] = gbm.Next().Close;
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}
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// Warm up
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Rema.Batch(source.AsSpan(), output.AsSpan(), 100);
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// This test verifies the method runs without throwing
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Assert.True(double.IsFinite(output[^1]));
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}
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[Fact]
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public void Rema_SpanBatch_HandlesNaN()
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{
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double[] source = [100, 110, double.NaN, 120, 130];
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double[] output = new double[5];
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Rema.Batch(source.AsSpan(), output.AsSpan(), 3);
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// All outputs should be finite
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foreach (var val in output)
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{
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Assert.True(double.IsFinite(val), $"Expected finite value but got {val}");
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}
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}
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[Fact]
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public void Chainability_Works()
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{
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var source = new TSeries();
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var rema = new Rema(source, 10);
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source.Add(new TValue(DateTime.UtcNow, 100));
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Assert.Equal(100, rema.Last.Value, 1e-10);
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}
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[Fact]
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public void Prime_SetsStateCorrectly()
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{
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var rema = new Rema(5);
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double[] history = [10, 20, 30, 40, 50];
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rema.Prime(history);
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// Verify against a fresh REMA fed with same data
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var verifyRema = new Rema(5);
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foreach (var val in history)
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{
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verifyRema.Update(new TValue(DateTime.UtcNow, val));
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}
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Assert.Equal(verifyRema.Last.Value, rema.Last.Value, 1e-10);
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Assert.Equal(verifyRema.IsHot, rema.IsHot);
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|
|
// Verify it continues correctly
|
|
rema.Update(new TValue(DateTime.UtcNow, 60));
|
|
verifyRema.Update(new TValue(DateTime.UtcNow, 60));
|
|
Assert.Equal(verifyRema.Last.Value, rema.Last.Value, 1e-10);
|
|
}
|
|
|
|
[Fact]
|
|
public void Prime_HandlesNaN_InHistory()
|
|
{
|
|
var rema = new Rema(5);
|
|
double[] history = [10, 20, double.NaN, 40, 50];
|
|
|
|
rema.Prime(history);
|
|
|
|
var verifyRema = new Rema(5);
|
|
foreach (var val in history)
|
|
{
|
|
verifyRema.Update(new TValue(DateTime.UtcNow, val));
|
|
}
|
|
|
|
Assert.Equal(verifyRema.Last.Value, rema.Last.Value, 1e-10);
|
|
}
|
|
|
|
[Fact]
|
|
public void Prime_AllNaNs_ReturnsNaN()
|
|
{
|
|
var rema = new Rema(5);
|
|
double[] history = [double.NaN, double.NaN, double.NaN];
|
|
|
|
rema.Prime(history);
|
|
|
|
Assert.True(double.IsNaN(rema.Last.Value));
|
|
}
|
|
|
|
[Fact]
|
|
public void Calculate_ReturnsCorrectResultsAndHotIndicator()
|
|
{
|
|
var series = new TSeries();
|
|
for (int i = 1; i <= 20; i++)
|
|
{
|
|
series.Add(DateTime.UtcNow, i * 10);
|
|
}
|
|
|
|
var (results, indicator) = Rema.Calculate(series, 5);
|
|
|
|
// Check results
|
|
Assert.Equal(20, results.Count);
|
|
|
|
// Verify against standard calculation
|
|
var verifyRema = new Rema(5);
|
|
var verifyResults = verifyRema.Update(series);
|
|
|
|
Assert.Equal(verifyResults.Last.Value, results.Last.Value, 1e-10);
|
|
Assert.Equal(verifyRema.Last.Value, indicator.Last.Value, 1e-10);
|
|
|
|
// Check indicator state
|
|
Assert.True(indicator.IsHot);
|
|
|
|
// Verify indicator continues correctly
|
|
indicator.Update(new TValue(DateTime.UtcNow, 210));
|
|
verifyRema.Update(new TValue(DateTime.UtcNow, 210));
|
|
Assert.Equal(verifyRema.Last.Value, indicator.Last.Value, 1e-10);
|
|
}
|
|
|
|
[Fact]
|
|
public void Rema_Batch_AllNaNs_ReturnsNaN()
|
|
{
|
|
double[] source = [double.NaN, double.NaN, double.NaN];
|
|
double[] output = new double[3];
|
|
|
|
Rema.Batch(source.AsSpan(), output.AsSpan(), 5);
|
|
|
|
// Should be all NaNs, not 0s
|
|
foreach (var val in output)
|
|
{
|
|
Assert.True(double.IsNaN(val), $"Expected NaN but got {val}");
|
|
}
|
|
}
|
|
|
|
[Fact]
|
|
public void Rema_AllModes_ProduceSameResult()
|
|
{
|
|
// Arrange
|
|
int period = 10;
|
|
double lambda = 0.5;
|
|
var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 123);
|
|
var bars = gbm.Fetch(1000, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
|
var series = bars.Close;
|
|
|
|
// 1. Batch Mode
|
|
var batchSeries = Rema.Batch(series, period, lambda);
|
|
double expected = batchSeries.Last.Value;
|
|
|
|
// 2. Span Mode
|
|
var tValues = series.Values.ToArray();
|
|
var spanInput = new ReadOnlySpan<double>(tValues);
|
|
var spanOutput = new double[tValues.Length];
|
|
Rema.Batch(spanInput, spanOutput, period, lambda);
|
|
double spanResult = spanOutput[^1];
|
|
|
|
// 3. Streaming Mode
|
|
var streamingInd = new Rema(period, lambda);
|
|
for (int i = 0; i < series.Count; i++)
|
|
{
|
|
streamingInd.Update(series[i]);
|
|
}
|
|
double streamingResult = streamingInd.Last.Value;
|
|
|
|
// 4. Eventing Mode
|
|
var pubSource = new TSeries();
|
|
var eventingInd = new Rema(pubSource, period, lambda);
|
|
for (int i = 0; i < series.Count; i++)
|
|
{
|
|
pubSource.Add(series[i]);
|
|
}
|
|
double eventingResult = eventingInd.Last.Value;
|
|
|
|
// Assert
|
|
Assert.Equal(expected, spanResult, precision: 9);
|
|
Assert.Equal(expected, streamingResult, precision: 9);
|
|
Assert.Equal(expected, eventingResult, precision: 9);
|
|
}
|
|
|
|
[Fact]
|
|
public void Rema_AllModes_ProduceSameResult_AfterResyncInterval()
|
|
{
|
|
// Guards against implementation drift between CalculateCore (batch/span)
|
|
// and Update(TValue) (streaming/eventing) over long runs.
|
|
int period = 10;
|
|
double lambda = 0.5;
|
|
int count = 12050; // Long-running consistency check
|
|
|
|
var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 321);
|
|
var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
|
var series = bars.Close;
|
|
|
|
// 1. Batch Mode
|
|
var batchSeries = Rema.Batch(series, period, lambda);
|
|
double expected = batchSeries.Last.Value;
|
|
|
|
// 2. Span Mode
|
|
var tValues = series.Values.ToArray();
|
|
var spanInput = new ReadOnlySpan<double>(tValues);
|
|
var spanOutput = new double[tValues.Length];
|
|
Rema.Batch(spanInput, spanOutput, period, lambda);
|
|
double spanResult = spanOutput[^1];
|
|
|
|
// 3. Streaming Mode
|
|
var streamingInd = new Rema(period, lambda);
|
|
for (int i = 0; i < series.Count; i++)
|
|
{
|
|
streamingInd.Update(series[i]);
|
|
}
|
|
|
|
double streamingResult = streamingInd.Last.Value;
|
|
|
|
// 4. Eventing Mode
|
|
var pubSource = new TSeries();
|
|
var eventingInd = new Rema(pubSource, period, lambda);
|
|
for (int i = 0; i < series.Count; i++)
|
|
{
|
|
pubSource.Add(series[i]);
|
|
}
|
|
|
|
double eventingResult = eventingInd.Last.Value;
|
|
|
|
Assert.Equal(expected, spanResult, precision: 9);
|
|
Assert.Equal(expected, streamingResult, precision: 9);
|
|
Assert.Equal(expected, eventingResult, precision: 9);
|
|
}
|
|
|
|
[Fact]
|
|
public void Prime_ThenUpdate_StateWorksCorrectly()
|
|
{
|
|
var rema = new Rema(5);
|
|
double[] history = [10, 20, 30, 40, 50];
|
|
|
|
rema.Prime(history);
|
|
double afterPrime = rema.Last.Value;
|
|
|
|
// After Prime, an isNew=true should advance the state
|
|
rema.Update(new TValue(DateTime.UtcNow, 60), isNew: true);
|
|
double afterNewBar = rema.Last.Value;
|
|
|
|
// Values should be different
|
|
Assert.NotEqual(afterPrime, afterNewBar);
|
|
|
|
// isNew=false with a different value should recalculate from previous state
|
|
rema.Update(new TValue(DateTime.UtcNow, 70), isNew: false);
|
|
double afterCorrection = rema.Last.Value;
|
|
|
|
// Correction with 70 should give different result than 60
|
|
Assert.NotEqual(afterNewBar, afterCorrection);
|
|
|
|
// isNew=false with original value (60) should restore to afterNewBar
|
|
rema.Update(new TValue(DateTime.UtcNow, 60), isNew: false);
|
|
Assert.Equal(afterNewBar, rema.Last.Value, 1e-10);
|
|
}
|
|
}
|