Files
QuanTAlib/lib/averages/trima/Trima.Tests.cs
T
Miha Kralj 967096d4f5 Refactor and optimize various components of QuanTAlib
- Removed WmaVector class to streamline weighted moving average calculations.
- Simplified RingBuffer implementation by removing unnecessary comments and improving clarity.
- Enhanced SIMD extensions for better performance and readability.
- Updated TBar and TBarSeries classes to improve property calculations and reduce overhead.
- Cleaned up TValue struct by removing redundant comments.
- Added comprehensive unit tests for IndicatorExtensions and TrimaIndicator to ensure functionality and correctness.
2025-12-04 13:49:05 -08:00

201 lines
6.0 KiB
C#

using Xunit;
namespace QuanTAlib.Tests;
public class TrimaTests
{
[Fact]
public void Trima_Constructor_ValidatesInput()
{
Assert.Throws<ArgumentException>(() => new Trima(0));
Assert.Throws<ArgumentException>(() => new Trima(-1));
var trima = new Trima(10);
Assert.NotNull(trima);
}
[Fact]
public void Trima_Calc_ReturnsValue()
{
var trima = new Trima(10);
Assert.Equal(0, trima.Value.Value);
TValue result = trima.Update(new TValue(DateTime.UtcNow, 100));
Assert.True(result.Value > 0);
Assert.Equal(result.Value, trima.Value.Value);
}
[Fact]
public void Trima_CalculatesCorrectAverage_Period4()
{
// Period 4 -> weights [1, 2, 2, 1], sum 6
var trima = new Trima(4);
trima.Update(new TValue(DateTime.UtcNow, 10));
trima.Update(new TValue(DateTime.UtcNow, 20));
trima.Update(new TValue(DateTime.UtcNow, 30));
var r1 = trima.Update(new TValue(DateTime.UtcNow, 40));
// (1*10 + 2*20 + 2*30 + 1*40) / 6 = 150 / 6 = 25
Assert.Equal(25.0, r1.Value, 1e-10);
var r2 = trima.Update(new TValue(DateTime.UtcNow, 50));
// (1*20 + 2*30 + 2*40 + 1*50) / 6 = 210 / 6 = 35
Assert.Equal(35.0, r2.Value, 1e-10);
}
[Fact]
public void Trima_CalculatesCorrectAverage_Period5()
{
// Period 5 -> weights [1, 2, 3, 2, 1], sum 9
var trima = new Trima(5);
trima.Update(new TValue(DateTime.UtcNow, 10));
trima.Update(new TValue(DateTime.UtcNow, 20));
trima.Update(new TValue(DateTime.UtcNow, 30));
trima.Update(new TValue(DateTime.UtcNow, 40));
var r1 = trima.Update(new TValue(DateTime.UtcNow, 50));
// (1*10 + 2*20 + 3*30 + 2*40 + 1*50) / 9 = (10 + 40 + 90 + 80 + 50) / 9 = 270 / 9 = 30
Assert.Equal(30.0, r1.Value, 1e-10);
}
[Fact]
public void Trima_IsHot_BecomesTrueWhenPeriodFilled()
{
var trima = new Trima(4);
Assert.False(trima.IsHot);
trima.Update(new TValue(DateTime.UtcNow, 10)); // 1
Assert.False(trima.IsHot);
trima.Update(new TValue(DateTime.UtcNow, 20)); // 2
Assert.False(trima.IsHot);
trima.Update(new TValue(DateTime.UtcNow, 30)); // 3
Assert.False(trima.IsHot);
trima.Update(new TValue(DateTime.UtcNow, 40)); // 4
Assert.True(trima.IsHot);
}
[Fact]
public void Trima_Update_IsNew_False_UpdatesValue()
{
var trima = new Trima(4);
trima.Update(new TValue(DateTime.UtcNow, 10));
trima.Update(new TValue(DateTime.UtcNow, 20));
trima.Update(new TValue(DateTime.UtcNow, 30));
// Update with 40
double val1 = trima.Update(new TValue(DateTime.UtcNow, 40), isNew: true).Value;
// Expected: 25 (as calculated above)
Assert.Equal(25.0, val1, 1e-10);
// Correct last value to 100 (was 40)
// New window: 10, 20, 30, 100
// Weights: 1, 2, 2, 1
// (10 + 40 + 60 + 100) / 6 = 210 / 6 = 35
double val2 = trima.Update(new TValue(DateTime.UtcNow, 100), isNew: false).Value;
Assert.Equal(35.0, val2, 1e-10);
}
[Fact]
public void Trima_Reset_ClearsState()
{
var trima = new Trima(5);
trima.Update(new TValue(DateTime.UtcNow, 100));
trima.Update(new TValue(DateTime.UtcNow, 105));
trima.Reset();
Assert.Equal(0, trima.Value.Value);
Assert.False(trima.IsHot);
// After reset, should accept new values
trima.Update(new TValue(DateTime.UtcNow, 50));
Assert.NotEqual(0, trima.Value.Value);
}
[Fact]
public void Trima_NaN_Input_UsesLastValidValue()
{
var trima = new Trima(5);
trima.Update(new TValue(DateTime.UtcNow, 100));
trima.Update(new TValue(DateTime.UtcNow, 110));
// Feed NaN - should use last valid value (110)
var resultAfterNaN = trima.Update(new TValue(DateTime.UtcNow, double.NaN));
Assert.True(double.IsFinite(resultAfterNaN.Value));
}
[Fact]
public void Trima_BatchCalc_MatchesIterativeCalc()
{
var trimaIterative = new Trima(10);
var trimaBatch = new Trima(10);
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
// Generate data
var series = new TSeries();
for (int i = 0; i < 100; i++)
{
var bar = gbm.Next(isNew: true);
series.Add(bar.Time, bar.Close);
}
// Calculate iteratively
var iterativeResults = new TSeries();
#pragma warning disable S4158 // Collection is known to be empty
foreach (var item in series)
{
iterativeResults.Add(trimaIterative.Update(item));
}
#pragma warning restore S4158
// Calculate batch
var batchResults = trimaBatch.Update(series);
// Compare
Assert.Equal(iterativeResults.Count, batchResults.Count);
#pragma warning disable S2583 // Condition always evaluates to false
for (int i = 0; i < iterativeResults.Count; i++)
{
Assert.Equal(iterativeResults[i].Value, batchResults[i].Value, 1e-10);
}
#pragma warning restore S2583
}
[Fact]
public void Trima_SpanCalc_MatchesTSeriesCalc()
{
var series = new TSeries();
double[] source = new double[100];
double[] output = new double[100];
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
for (int i = 0; i < 100; i++)
{
var bar = gbm.Next(isNew: true);
source[i] = bar.Close;
series.Add(bar.Time, bar.Close);
}
// Calculate with TSeries API
var tseriesResult = Trima.Calculate(series, 10);
// Calculate with Span API
Trima.Calculate(source.AsSpan(), output.AsSpan(), 10);
// Compare results
for (int i = 0; i < 100; i++)
{
Assert.Equal(tseriesResult[i].Value, output[i], 1e-10);
}
}
}