mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-12 23:58:04 +00:00
Miha Kralj
ed5e5c8209
- Implement tests for HMA (Hull Moving Average) indicator to verify default settings, history depth calculations, and value computations during updates. - Create tests for KAMA (Kaufman Adaptive Moving Average) indicator, ensuring correct defaults, history depth, and value calculations. - Add tests for SMA (Simple Moving Average) indicator, checking default values, history depth, and value computations. - Develop tests for T3 (Tillson T3 Moving Average) indicator, validating defaults, history depth, and value calculations. - Implement tests for TEMA (Triple Exponential Moving Average) indicator, ensuring correct defaults and value computations. - Create tests for TRIMA (Triangular Moving Average) indicator, verifying defaults, history depth, and value calculations. - Add tests for WMA (Weighted Moving Average) indicator, checking default values, history depth, and value computations.
510 lines
15 KiB
C#
510 lines
15 KiB
C#
namespace QuanTAlib.Tests;
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#pragma warning disable S2245 // Random is acceptable for simulation/testing purposes
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public class SmaTests
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{
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[Fact]
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public void Sma_Constructor_ValidatesInput()
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{
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Assert.Throws<ArgumentException>(() => new Sma(0));
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Assert.Throws<ArgumentException>(() => new Sma(-1));
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var sma = new Sma(10);
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Assert.NotNull(sma);
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}
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[Fact]
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public void Sma_Calc_ReturnsValue()
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{
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var sma = new Sma(10);
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Assert.Equal(0, sma.Last.Value);
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TValue result = sma.Update(new TValue(DateTime.UtcNow, 100));
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Assert.True(result.Value > 0);
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Assert.Equal(result.Value, sma.Last.Value);
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}
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[Fact]
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public void Sma_FirstValue_ReturnsItself()
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{
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var sma = new Sma(10);
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TValue result = sma.Update(new TValue(DateTime.UtcNow, 100));
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Assert.Equal(100.0, result.Value, 1e-10);
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}
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[Fact]
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public void Sma_Calc_IsNew_AcceptsParameter()
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{
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var sma = new Sma(10);
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sma.Update(new TValue(DateTime.UtcNow, 100), isNew: true);
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double value1 = sma.Last.Value;
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sma.Update(new TValue(DateTime.UtcNow, 200), isNew: true);
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double value2 = sma.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 Sma_Calc_IsNew_False_UpdatesValue()
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{
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var sma = new Sma(10);
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sma.Update(new TValue(DateTime.UtcNow, 100));
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sma.Update(new TValue(DateTime.UtcNow, 110), isNew: true);
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double beforeUpdate = sma.Last.Value;
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sma.Update(new TValue(DateTime.UtcNow, 120), isNew: false);
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double afterUpdate = sma.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 Sma_Reset_ClearsState()
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{
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var sma = new Sma(10);
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sma.Update(new TValue(DateTime.UtcNow, 100));
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sma.Update(new TValue(DateTime.UtcNow, 105));
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double valueBefore = sma.Last.Value;
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sma.Reset();
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Assert.Equal(0, sma.Last.Value);
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// After reset, should accept new values
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sma.Update(new TValue(DateTime.UtcNow, 50));
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Assert.NotEqual(0, sma.Last.Value);
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Assert.NotEqual(valueBefore, sma.Last.Value);
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}
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[Fact]
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public void Sma_Properties_Accessible()
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{
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var sma = new Sma(10);
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Assert.Equal(0, sma.Last.Value);
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Assert.False(sma.IsHot);
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sma.Update(new TValue(DateTime.UtcNow, 100));
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Assert.NotEqual(0, sma.Last.Value);
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}
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[Fact]
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public void Sma_IsHot_BecomesTrueWhenBufferFull()
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{
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var sma = new Sma(5);
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Assert.False(sma.IsHot);
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for (int i = 1; i <= 4; i++)
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{
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sma.Update(new TValue(DateTime.UtcNow, i * 10));
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Assert.False(sma.IsHot);
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}
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sma.Update(new TValue(DateTime.UtcNow, 50));
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Assert.True(sma.IsHot);
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}
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[Fact]
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public void Sma_CalculatesCorrectAverage()
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{
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var sma = new Sma(5);
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sma.Update(new TValue(DateTime.UtcNow, 10));
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sma.Update(new TValue(DateTime.UtcNow, 20));
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sma.Update(new TValue(DateTime.UtcNow, 30));
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sma.Update(new TValue(DateTime.UtcNow, 40));
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sma.Update(new TValue(DateTime.UtcNow, 50));
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// SMA(5) of 10,20,30,40,50 = 150/5 = 30
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Assert.Equal(30.0, sma.Last.Value, 1e-10);
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}
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[Fact]
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public void Sma_SlidingWindow_Works()
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{
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var sma = new Sma(3);
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sma.Update(new TValue(DateTime.UtcNow, 10));
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sma.Update(new TValue(DateTime.UtcNow, 20));
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sma.Update(new TValue(DateTime.UtcNow, 30));
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// SMA(3) of 10,20,30 = 60/3 = 20
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Assert.Equal(20.0, sma.Last.Value, 1e-10);
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sma.Update(new TValue(DateTime.UtcNow, 40));
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// SMA(3) of 20,30,40 = 90/3 = 30
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Assert.Equal(30.0, sma.Last.Value, 1e-10);
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sma.Update(new TValue(DateTime.UtcNow, 50));
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// SMA(3) of 30,40,50 = 120/3 = 40
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Assert.Equal(40.0, sma.Last.Value, 1e-10);
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}
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[Fact]
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public void Sma_IterativeCorrections_RestoreToOriginalState()
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{
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var sma = new Sma(5);
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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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sma.Update(tenthInput, isNew: true);
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}
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// Remember SMA state after 10 values
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double smaAfterTen = sma.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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sma.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 finalSma = sma.Update(tenthInput, isNew: false);
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// SMA should match the original state after 10 values
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Assert.Equal(smaAfterTen, finalSma.Value, 1e-10);
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}
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[Fact]
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public void Sma_BatchCalc_MatchesIterativeCalc()
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{
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var smaIterative = new Sma(10);
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var smaBatch = new Sma(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(smaIterative.Update(item));
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}
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// Calculate batch
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var batchResults = smaBatch.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 Sma_Result_ImplicitConversionToDouble()
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{
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var sma = new Sma(10);
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sma.Update(new TValue(DateTime.UtcNow, 100));
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// This should compile and work because TValue has implicit conversion to double
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double result = sma.Last.Value;
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Assert.Equal(100.0, result, 1e-10);
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}
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[Fact]
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public void Sma_NaN_Input_UsesLastValidValue()
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{
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var sma = new Sma(5);
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// Feed some valid values
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sma.Update(new TValue(DateTime.UtcNow, 100));
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sma.Update(new TValue(DateTime.UtcNow, 110));
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// Feed NaN - should use last valid value (110)
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var resultAfterNaN = sma.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 Sma_Infinity_Input_UsesLastValidValue()
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{
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var sma = new Sma(5);
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// Feed some valid values
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sma.Update(new TValue(DateTime.UtcNow, 100));
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sma.Update(new TValue(DateTime.UtcNow, 110));
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// Feed positive infinity - should use last valid value
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var resultAfterPosInf = sma.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 = sma.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 Sma_MultipleNaN_ContinuesWithLastValid()
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{
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var sma = new Sma(5);
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// Feed valid values
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sma.Update(new TValue(DateTime.UtcNow, 100));
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sma.Update(new TValue(DateTime.UtcNow, 110));
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sma.Update(new TValue(DateTime.UtcNow, 120));
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// Feed multiple NaN values
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var r1 = sma.Update(new TValue(DateTime.UtcNow, double.NaN));
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var r2 = sma.Update(new TValue(DateTime.UtcNow, double.NaN));
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var r3 = sma.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 Sma_BatchCalc_HandlesNaN()
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{
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var sma = new Sma(5);
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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 = sma.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 Sma_Reset_ClearsLastValidValue()
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{
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var sma = new Sma(5);
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// Feed values including NaN
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sma.Update(new TValue(DateTime.UtcNow, 100));
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sma.Update(new TValue(DateTime.UtcNow, double.NaN));
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// Reset
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sma.Reset();
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// After reset, first valid value should establish new baseline
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var result = sma.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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[Fact]
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public void Sma_StaticCalculate_Works()
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{
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var series = new TSeries();
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series.Add(DateTime.UtcNow.Ticks, 10);
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series.Add(DateTime.UtcNow.Ticks + 1, 20);
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series.Add(DateTime.UtcNow.Ticks + 2, 30);
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series.Add(DateTime.UtcNow.Ticks + 3, 40);
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series.Add(DateTime.UtcNow.Ticks + 4, 50);
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var results = Sma.Calculate(series, 3);
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Assert.Equal(5, results.Count);
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// SMA(3) for last value: (30+40+50)/3 = 40
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Assert.Equal(40.0, results.Last.Value, 1e-10);
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}
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[Fact]
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public void Sma_Period1_ReturnsInputValues()
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{
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var sma = new Sma(1);
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Assert.Equal(100.0, sma.Update(new TValue(DateTime.UtcNow, 100)).Value, 1e-10);
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Assert.Equal(200.0, sma.Update(new TValue(DateTime.UtcNow, 200)).Value, 1e-10);
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Assert.Equal(150.0, sma.Update(new TValue(DateTime.UtcNow, 150)).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 Sma_SpanCalc_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>(() => Sma.Calculate(source.AsSpan(), output.AsSpan(), 0));
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Assert.Throws<ArgumentException>(() => Sma.Calculate(source.AsSpan(), output.AsSpan(), -1));
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// Output must be same length as source
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Assert.Throws<ArgumentException>(() => Sma.Calculate(source.AsSpan(), wrongSizeOutput.AsSpan(), 3));
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}
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[Fact]
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public void Sma_SpanCalc_MatchesTSeriesCalc()
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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 = Sma.Calculate(series, 10);
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// Calculate with Span API
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Sma.Calculate(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-10);
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}
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}
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[Fact]
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public void Sma_SpanCalc_CalculatesCorrectly()
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{
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double[] source = [10, 20, 30, 40, 50];
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double[] output = new double[5];
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Sma.Calculate(source.AsSpan(), output.AsSpan(), 3);
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// SMA(3) warmup: 10, (10+20)/2=15, (10+20+30)/3=20, then sliding: (20+30+40)/3=30, (30+40+50)/3=40
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Assert.Equal(10.0, output[0], 1e-10);
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Assert.Equal(15.0, output[1], 1e-10);
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Assert.Equal(20.0, output[2], 1e-10);
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Assert.Equal(30.0, output[3], 1e-10);
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Assert.Equal(40.0, output[4], 1e-10);
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}
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[Fact]
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public void Sma_SpanCalc_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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source[i] = gbm.Next().Close;
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// Warm up
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Sma.Calculate(source.AsSpan(), output.AsSpan(), 100);
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// This test verifies the method runs without throwing
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// (allocation is measured by BenchmarkDotNet, not unit tests)
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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 Sma_SpanCalc_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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Sma.Calculate(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 Sma_SpanCalc_Period1_ReturnsInput()
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{
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double[] source = [10, 20, 30, 40, 50];
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double[] output = new double[5];
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Sma.Calculate(source.AsSpan(), output.AsSpan(), 1);
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for (int i = 0; i < source.Length; i++)
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{
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Assert.Equal(source[i], output[i], 1e-10);
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}
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}
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[Fact]
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public void Sma_AllModes_ProduceSameResult()
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{
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// Arrange
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int period = 10;
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 123);
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var bars = gbm.Fetch(1000, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var series = bars.Close;
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// 1. Batch Mode
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var batchSeries = Sma.Calculate(series, period);
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double expected = batchSeries.Last.Value;
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// 2. Span Mode
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var tValues = series.Values.ToArray();
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var spanInput = new ReadOnlySpan<double>(tValues);
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var spanOutput = new double[tValues.Length];
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Sma.Calculate(spanInput, spanOutput, period);
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double spanResult = spanOutput[^1];
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// 3. Streaming Mode
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var streamingInd = new Sma(period);
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for (int i = 0; i < series.Count; i++)
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{
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streamingInd.Update(series[i]);
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}
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double streamingResult = streamingInd.Last.Value;
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// 4. Eventing Mode
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var pubSource = new TSeries();
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var eventingInd = new Sma(pubSource, period);
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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);
|
|
}
|
|
}
|