Files
QuanTAlib/lib/trends_IIR/trama/Trama.Validation.Tests.cs
T
Miha Kralj 7253f61299 Add TRAMA implementation and comprehensive tests
- Implemented the TRAMA (Trend Regularity Adaptive Moving Average) class with adaptive EMA logic.
- Added unit tests for TRAMA functionality, including constructor validation, basic calculations, state management, and robustness checks.
- Created validation tests to ensure consistency across different modes of operation (streaming, batch, and static calculations).
- Enhanced documentation for TRAMA, including performance profiles and quality metrics.
- Updated workspace configuration by removing unnecessary folder references.
2026-02-21 20:45:38 -08:00

168 lines
4.6 KiB
C#

using Xunit;
namespace QuanTAlib.Tests;
public class TramaValidationTests
{
private const int DefaultPeriod = 14;
private const long Seed = 54321;
private static readonly TimeSpan Step = TimeSpan.FromMinutes(1);
private static TSeries GetTestSeries(int count = 500)
{
var gbm = new GBM();
var bars = gbm.Fetch(count, Seed, Step);
return bars.Close;
}
// ── Self-consistency: no external library implements TRAMA ─────
[Fact]
public void Streaming_Matches_SpanBatch()
{
var series = GetTestSeries(500);
// Streaming
var trama = new Trama(DefaultPeriod);
var streamResults = new List<double>();
for (int i = 0; i < series.Count; i++)
{
streamResults.Add(trama.Update(series[i]).Value);
}
// Span batch
var output = new double[series.Count];
Trama.Batch(series.Values, output, DefaultPeriod);
for (int i = 0; i < output.Length; i++)
{
Assert.Equal(streamResults[i], output[i], 1e-9);
}
}
[Fact]
public void Streaming_Matches_TSeries()
{
var series = GetTestSeries(500);
// Streaming
var trama1 = new Trama(DefaultPeriod);
var streamResults = new List<double>();
for (int i = 0; i < series.Count; i++)
{
streamResults.Add(trama1.Update(series[i]).Value);
}
// TSeries
var trama2 = new Trama(DefaultPeriod);
var batchResults = trama2.Update(series);
for (int i = 0; i < batchResults.Count; i++)
{
Assert.Equal(streamResults[i], batchResults.Values[i], 1e-9);
}
}
[Fact]
public void StaticCalculate_Matches_Streaming()
{
var series = GetTestSeries(500);
// Streaming
var trama = new Trama(DefaultPeriod);
var streamResults = new List<double>();
for (int i = 0; i < series.Count; i++)
{
streamResults.Add(trama.Update(series[i]).Value);
}
// Static Calculate
var (calcResults, _) = Trama.Calculate(series, DefaultPeriod);
for (int i = 0; i < calcResults.Count; i++)
{
Assert.Equal(streamResults[i], calcResults.Values[i], 1e-9);
}
}
[Theory]
[InlineData(5)]
[InlineData(14)]
[InlineData(30)]
[InlineData(50)]
public void AllModes_Match_AcrossPeriods(int period)
{
var series = GetTestSeries(300);
// Streaming
var trama = new Trama(period);
var streamResults = new List<double>();
for (int i = 0; i < series.Count; i++)
{
streamResults.Add(trama.Update(series[i]).Value);
}
// Span batch
var output = new double[series.Count];
Trama.Batch(series.Values, output, period);
for (int i = 0; i < output.Length; i++)
{
Assert.Equal(streamResults[i], output[i], 1e-9);
}
}
[Fact]
public void Prime_Matches_Streaming()
{
var series = GetTestSeries(500);
// Streaming
var trama1 = new Trama(DefaultPeriod);
for (int i = 0; i < series.Count; i++)
{
trama1.Update(series[i]);
}
// Prime
var trama2 = new Trama(DefaultPeriod);
trama2.Prime(series.Values);
Assert.Equal(trama1.Last.Value, trama2.Last.Value, 1e-9);
}
[Fact]
public void DirectionalCorrectness_UpTrend()
{
// Strong uptrend should produce TRAMA values between start and current price
var trama = new Trama(DefaultPeriod);
double startPrice = 100.0;
for (int i = 0; i < 100; i++)
{
trama.Update(new TValue(DateTime.UtcNow.AddMinutes(i).Ticks, startPrice + i));
}
double lastPrice = startPrice + 99;
// TRAMA should lag behind price but be above start
Assert.True(trama.Last.Value > startPrice, "TRAMA should be above start price in uptrend");
Assert.True(trama.Last.Value <= lastPrice, "TRAMA should not exceed current price in uptrend");
}
[Fact]
public void DirectionalCorrectness_DownTrend()
{
var trama = new Trama(DefaultPeriod);
double startPrice = 200.0;
for (int i = 0; i < 100; i++)
{
trama.Update(new TValue(DateTime.UtcNow.AddMinutes(i).Ticks, startPrice - i));
}
double lastPrice = startPrice - 99;
Assert.True(trama.Last.Value < startPrice, "TRAMA should be below start price in downtrend");
Assert.True(trama.Last.Value >= lastPrice, "TRAMA should not go below current price in downtrend");
}
}