Files
2026-03-12 19:37:50 +00:00

341 lines
8.8 KiB
C#

namespace QuanTAlib.Tests;
public class MraeTests
{
[Fact]
public void Constructor_ValidatesInput()
{
Assert.Throws<ArgumentException>(() => new Mrae(0));
Assert.Throws<ArgumentException>(() => new Mrae(-1));
var mrae = new Mrae(10);
Assert.NotNull(mrae);
}
[Fact]
public void Properties_Accessible()
{
var mrae = new Mrae(10);
Assert.Equal(0, mrae.Last.Value);
Assert.False(mrae.IsHot);
Assert.Contains("Mrae", mrae.Name, StringComparison.Ordinal);
mrae.Update(100, 105);
Assert.NotEqual(0, mrae.Last.Value);
}
[Fact]
public void IsHot_BecomesTrueWhenBufferFull()
{
const int period = 5;
var mrae = new Mrae(period);
for (int i = 1; i <= period - 1; i++)
{
Assert.False(mrae.IsHot, $"IsHot should be false at index {i}");
mrae.Update(i * 10, (i * 10) + 5);
}
mrae.Update(period * 10, (period * 10) + 5);
Assert.True(mrae.IsHot, "IsHot should be true after period updates");
}
[Fact]
public void Mrae_CalculatesCorrectly()
{
var mrae = new Mrae(3);
// |100 - 110| / |100| = 10/100 = 0.1
var res1 = mrae.Update(100, 110);
Assert.Equal(0.1, res1.Value, 10);
// |200 - 220| / |200| = 20/200 = 0.1, Mean = (0.1 + 0.1) / 2 = 0.1
var res2 = mrae.Update(200, 220);
Assert.Equal(0.1, res2.Value, 10);
// |50 - 60| / |50| = 10/50 = 0.2, Mean = (0.1 + 0.1 + 0.2) / 3 = 0.133...
var res3 = mrae.Update(50, 60);
Assert.Equal(0.4 / 3.0, res3.Value, 10);
}
[Fact]
public void Mrae_PerfectPrediction_ReturnsZero()
{
var mrae = new Mrae(5);
for (int i = 1; i <= 10; i++)
{
mrae.Update(i * 10, i * 10); // Perfect prediction
}
Assert.Equal(0.0, mrae.Last.Value, 10);
}
[Fact]
public void Mrae_ProportionalError_ReturnsConstant()
{
var mrae = new Mrae(5);
// 10% error for all
for (int i = 1; i <= 10; i++)
{
mrae.Update(i * 100, i * 110); // 10% overestimate
}
Assert.Equal(0.1, mrae.Last.Value, 10);
}
[Fact]
public void Calc_IsNew_AcceptsParameter()
{
var mrae = new Mrae(10);
mrae.Update(100, 110, isNew: true);
double value1 = mrae.Last.Value;
mrae.Update(100, 120, isNew: true);
double value2 = mrae.Last.Value;
Assert.NotEqual(value1, value2);
}
[Fact]
public void Calc_IsNew_False_UpdatesValue()
{
var mrae = new Mrae(10);
mrae.Update(100, 110);
mrae.Update(100, 120, isNew: true);
double beforeUpdate = mrae.Last.Value;
mrae.Update(100, 130, isNew: false);
double afterUpdate = mrae.Last.Value;
Assert.NotEqual(beforeUpdate, afterUpdate);
}
[Fact]
public void IterativeCorrections_RestoreToOriginalState()
{
var mrae = new Mrae(5);
double tenthActual = 0;
double tenthPredicted = 0;
// Feed 10 updates
for (int i = 1; i <= 10; i++)
{
tenthActual = i * 100;
tenthPredicted = (i * 100) + 10;
mrae.Update(tenthActual, tenthPredicted);
}
double stateAfterTen = mrae.Last.Value;
// Apply 5 corrections with isNew=false
for (int i = 0; i < 5; i++)
{
mrae.Update(100 + i, 200 + i, isNew: false);
}
// Restore to original values
mrae.Update(tenthActual, tenthPredicted, isNew: false);
Assert.Equal(stateAfterTen, mrae.Last.Value, 10);
}
[Fact]
public void Reset_ClearsState()
{
var mrae = new Mrae(5);
for (int i = 1; i <= 10; i++)
{
mrae.Update(i * 10, (i * 10) + 5);
}
Assert.True(mrae.IsHot);
mrae.Reset();
Assert.False(mrae.IsHot);
Assert.Equal(0, mrae.Last.Value);
}
[Fact]
public void NaN_Input_UsesLastValidValue()
{
var mrae = new Mrae(5);
mrae.Update(100, 110);
mrae.Update(110, 120);
mrae.Update(120, 130);
var result = mrae.Update(double.NaN, double.NaN);
Assert.True(double.IsFinite(result.Value));
}
[Fact]
public void Infinity_Input_UsesLastValidValue()
{
var mrae = new Mrae(5);
mrae.Update(100, 110);
mrae.Update(110, 120);
var result = mrae.Update(double.PositiveInfinity, double.NegativeInfinity);
Assert.True(double.IsFinite(result.Value));
}
[Fact]
public void MultipleNaN_ContinuesWithLastValid()
{
var mrae = new Mrae(5);
mrae.Update(100, 110);
mrae.Update(110, 120);
mrae.Update(120, 130);
var r1 = mrae.Update(double.NaN, double.NaN);
var r2 = mrae.Update(double.NaN, double.NaN);
var r3 = mrae.Update(double.NaN, double.NaN);
Assert.True(double.IsFinite(r1.Value));
Assert.True(double.IsFinite(r2.Value));
Assert.True(double.IsFinite(r3.Value));
}
[Fact]
public void Mrae_Throws_On_Single_Input()
{
var mrae = new Mrae(10);
Assert.Throws<NotSupportedException>(() => mrae.Update(new TValue(DateTime.UtcNow, 1)));
Assert.Throws<NotSupportedException>(() => mrae.Update(new TSeries()));
Assert.Throws<NotSupportedException>(() => mrae.Prime([1, 2, 3]));
}
[Fact]
public void BatchSpan_MatchesStreaming()
{
int period = 5;
int count = 100;
var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 123);
double[] actual = new double[count];
double[] predicted = new double[count];
for (int i = 0; i < count; i++)
{
var bar = gbm.Next();
actual[i] = bar.Close;
predicted[i] = (bar.Close * 1.05) + 2;
}
// Streaming
var mrae = new Mrae(period);
var streamingResults = new double[count];
for (int i = 0; i < count; i++)
{
streamingResults[i] = mrae.Update(actual[i], predicted[i]).Value;
}
// Batch
double[] batchResults = new double[count];
Mrae.Batch(actual, predicted, batchResults, period);
// Compare
for (int i = 0; i < count; i++)
{
Assert.Equal(streamingResults[i], batchResults[i], 9);
}
}
[Fact]
public void BatchSpan_ValidatesInput()
{
double[] actual = [10, 20, 30, 40, 50];
double[] predicted = [11, 22, 33, 44, 55];
double[] output = new double[5];
double[] wrongSizeOutput = new double[3];
double[] wrongSizePredicted = new double[3];
Assert.Throws<ArgumentException>(() =>
Mrae.Batch(actual.AsSpan(), predicted.AsSpan(), output.AsSpan(), 0));
Assert.Throws<ArgumentException>(() =>
Mrae.Batch(actual.AsSpan(), predicted.AsSpan(), output.AsSpan(), -1));
Assert.Throws<ArgumentException>(() =>
Mrae.Batch(actual.AsSpan(), predicted.AsSpan(), wrongSizeOutput.AsSpan(), 3));
Assert.Throws<ArgumentException>(() =>
Mrae.Batch(actual.AsSpan(), wrongSizePredicted.AsSpan(), output.AsSpan(), 3));
}
[Fact]
public void Calculate_Works()
{
var actual = new TSeries();
var predicted = new TSeries();
var now = DateTime.UtcNow;
for (int i = 1; i <= 10; i++)
{
actual.Add(now.AddMinutes(i), i * 100);
predicted.Add(now.AddMinutes(i), i * 110); // 10% error
}
var results = Mrae.Batch(actual, predicted, 3);
Assert.Equal(10, results.Count);
Assert.Equal(0.1, results.Last.Value, 10);
}
[Fact]
public void Calculate_ValidatesMismatchedLengths()
{
var actual = new TSeries();
var predicted = new TSeries();
for (int i = 1; i <= 10; i++)
{
actual.Add(DateTime.UtcNow, i * 10);
}
for (int i = 1; i <= 5; i++)
{
predicted.Add(DateTime.UtcNow, i * 10);
}
Assert.Throws<ArgumentException>(() => Mrae.Batch(actual, predicted, 3));
}
[Fact]
public void BatchSpan_HandlesNaN()
{
double[] actual = [100, 110, double.NaN, 130, 140];
double[] predicted = [105, 115, 125, double.NaN, 145];
double[] output = new double[5];
Mrae.Batch(actual, predicted, output, 3);
foreach (var val in output)
{
Assert.True(double.IsFinite(val), $"Expected finite value but got {val}");
}
}
[Fact]
public void Mrae_Resync_Works()
{
var mrae = new Mrae(5);
// Force many updates to trigger resync
for (int i = 1; i <= 1100; i++)
{
mrae.Update(100, 110); // 10% error
}
Assert.Equal(0.1, mrae.Last.Value, 10);
}
}