mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-13 08:08:05 +00:00
- 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.
180 lines
4.9 KiB
C#
180 lines
4.9 KiB
C#
using System;
|
|
using System.Linq;
|
|
using Xunit;
|
|
|
|
namespace QuanTAlib.Tests;
|
|
|
|
public class AlmaTests
|
|
{
|
|
[Fact]
|
|
public void Alma_Constructor_ValidatesInput()
|
|
{
|
|
Assert.Throws<ArgumentException>(() => new Alma(0));
|
|
Assert.Throws<ArgumentException>(() => new Alma(10, sigma: 0));
|
|
|
|
var alma = new Alma(10);
|
|
Assert.NotNull(alma);
|
|
}
|
|
|
|
[Fact]
|
|
public void Alma_Calc_ReturnsValue()
|
|
{
|
|
var alma = new Alma(10);
|
|
TValue result = alma.Update(new TValue(DateTime.UtcNow, 100));
|
|
Assert.True(result.Value > 0);
|
|
}
|
|
|
|
[Fact]
|
|
public void Alma_IsHot_BecomesTrueWhenBufferFull()
|
|
{
|
|
var alma = new Alma(5);
|
|
|
|
Assert.False(alma.IsHot);
|
|
|
|
for (int i = 0; i < 4; i++)
|
|
{
|
|
alma.Update(new TValue(DateTime.UtcNow, 100));
|
|
Assert.False(alma.IsHot);
|
|
}
|
|
|
|
alma.Update(new TValue(DateTime.UtcNow, 100));
|
|
Assert.True(alma.IsHot);
|
|
}
|
|
|
|
[Fact]
|
|
public void Alma_StreamingMatchesBatch()
|
|
{
|
|
var almaStreaming = new Alma(10);
|
|
var almaBatch = new Alma(10);
|
|
var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 0.2, seed: 42);
|
|
var series = new TSeries();
|
|
|
|
for (int i = 0; i < 100; i++)
|
|
{
|
|
var bar = gbm.Next(isNew: true);
|
|
series.Add(bar.Time, bar.Close);
|
|
}
|
|
|
|
// Streaming
|
|
var streamingResults = new TSeries();
|
|
foreach (var item in series)
|
|
{
|
|
streamingResults.Add(almaStreaming.Update(item));
|
|
}
|
|
|
|
// Batch
|
|
var batchResults = almaBatch.Update(series);
|
|
|
|
Assert.Equal(streamingResults.Count, batchResults.Count);
|
|
for (int i = 0; i < streamingResults.Count; i++)
|
|
{
|
|
Assert.Equal(streamingResults[i].Value, batchResults[i].Value, 1e-9);
|
|
}
|
|
}
|
|
|
|
[Fact]
|
|
public void Alma_StaticCalculate_MatchesInstance()
|
|
{
|
|
var series = new TSeries();
|
|
var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 0.2, seed: 42);
|
|
for (int i = 0; i < 100; i++)
|
|
{
|
|
var bar = gbm.Next(isNew: true);
|
|
series.Add(bar.Time, bar.Close);
|
|
}
|
|
|
|
var instanceResults = new Alma(10).Update(series);
|
|
var staticResults = Alma.Calculate(series, 10);
|
|
|
|
for (int i = 0; i < instanceResults.Count; i++)
|
|
{
|
|
Assert.Equal(instanceResults[i].Value, staticResults[i].Value, 1e-9);
|
|
}
|
|
}
|
|
|
|
[Fact]
|
|
public void Alma_SpanCalculate_MatchesSeries()
|
|
{
|
|
var series = new TSeries();
|
|
var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 0.2, seed: 42);
|
|
for (int i = 0; i < 100; i++)
|
|
{
|
|
var bar = gbm.Next(isNew: true);
|
|
series.Add(bar.Time, bar.Close);
|
|
}
|
|
|
|
var seriesResults = Alma.Calculate(series, 10);
|
|
|
|
double[] input = series.Values.ToArray();
|
|
double[] output = new double[input.Length];
|
|
|
|
Alma.Calculate(input.AsSpan(), output.AsSpan(), 10);
|
|
|
|
for (int i = 0; i < input.Length; i++)
|
|
{
|
|
Assert.Equal(seriesResults[i].Value, output[i], 1e-9);
|
|
}
|
|
}
|
|
|
|
[Fact]
|
|
public void Alma_Update_IsNewFalse_CorrectsValue()
|
|
{
|
|
var alma = new Alma(10);
|
|
var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 0.2, seed: 42);
|
|
|
|
// Feed initial data
|
|
for (int i = 0; i < 20; i++)
|
|
{
|
|
var bar = gbm.Next(isNew: true);
|
|
alma.Update(new TValue(bar.Time, bar.Close), isNew: true);
|
|
}
|
|
|
|
// Update with isNew=false (correction)
|
|
var newBar = gbm.Next(isNew: true);
|
|
alma.Update(new TValue(newBar.Time, newBar.Close), isNew: true);
|
|
|
|
double valueAfterCommit = alma.Last.Value;
|
|
|
|
// Now update the SAME bar with a different value
|
|
alma.Update(new TValue(newBar.Time, newBar.Close + 10.0), isNew: false);
|
|
|
|
double valueAfterCorrection = alma.Last.Value;
|
|
|
|
Assert.NotEqual(valueAfterCommit, valueAfterCorrection);
|
|
|
|
// Now restore original value
|
|
alma.Update(new TValue(newBar.Time, newBar.Close), isNew: false);
|
|
|
|
Assert.Equal(valueAfterCommit, alma.Last.Value, 1e-9);
|
|
}
|
|
|
|
[Fact]
|
|
public void Alma_NaN_Input_UsesLastValidValue()
|
|
{
|
|
var alma = new Alma(5);
|
|
|
|
alma.Update(new TValue(DateTime.UtcNow, 100));
|
|
alma.Update(new TValue(DateTime.UtcNow, 110));
|
|
|
|
var resultAfterNaN = alma.Update(new TValue(DateTime.UtcNow, double.NaN));
|
|
|
|
Assert.True(double.IsFinite(resultAfterNaN.Value));
|
|
Assert.NotEqual(0, resultAfterNaN.Value);
|
|
}
|
|
|
|
[Fact]
|
|
public void Alma_Reset_ClearsState()
|
|
{
|
|
var alma = new Alma(10);
|
|
alma.Update(new TValue(DateTime.UtcNow, 100));
|
|
alma.Update(new TValue(DateTime.UtcNow, 110));
|
|
|
|
Assert.True(alma.Last.Value > 0);
|
|
|
|
alma.Reset();
|
|
|
|
Assert.Equal(0, alma.Last.Value);
|
|
Assert.False(alma.IsHot);
|
|
}
|
|
}
|