Files
QuanTAlib/lib/errors/mse/Mse.Tests.cs
2026-02-10 21:33:16 -08:00

312 lines
8.0 KiB
C#

namespace QuanTAlib.Tests;
public class MseTests
{
[Fact]
public void Constructor_ValidatesInput()
{
Assert.Throws<ArgumentException>(() => new Mse(0));
Assert.Throws<ArgumentException>(() => new Mse(-1));
var mse = new Mse(10);
Assert.NotNull(mse);
}
[Fact]
public void Properties_Accessible()
{
var mse = new Mse(10);
Assert.Equal(0, mse.Last.Value);
Assert.False(mse.IsHot);
Assert.Contains("Mse", mse.Name, StringComparison.Ordinal);
mse.Update(100, 105);
Assert.NotEqual(0, mse.Last.Value);
}
[Fact]
public void IsHot_BecomesTrueWhenBufferFull()
{
const int period = 5;
var mse = new Mse(period);
for (int i = 0; i < period - 1; i++)
{
Assert.False(mse.IsHot, $"IsHot should be false at index {i}");
mse.Update(i * 10, i * 10 + 5);
}
mse.Update((period - 1) * 10, (period - 1) * 10 + 5);
Assert.True(mse.IsHot, "IsHot should be true after period updates");
}
[Fact]
public void Mse_CalculatesCorrectly()
{
var mse = new Mse(3);
// (10 - 15)² = 25
var res1 = mse.Update(10, 15);
Assert.Equal(25.0, res1.Value, 10);
// (20 - 30)² = 100, Mean = (25 + 100) / 2 = 62.5
var res2 = mse.Update(20, 30);
Assert.Equal(62.5, res2.Value, 10);
// (30 - 25)² = 25, Mean = (25 + 100 + 25) / 3 = 50
var res3 = mse.Update(30, 25);
Assert.Equal(50.0, res3.Value, 10);
// (40 - 35)² = 25, Window slides: (100 + 25 + 25) / 3 = 50
var res4 = mse.Update(40, 35);
Assert.Equal(50.0, res4.Value, 10);
}
[Fact]
public void Mse_PerfectPrediction_ReturnsZero()
{
var mse = new Mse(5);
for (int i = 0; i < 10; i++)
{
mse.Update(i * 10, i * 10); // Perfect prediction
}
Assert.Equal(0.0, mse.Last.Value, 10);
}
[Fact]
public void Mse_ConstantError_ReturnsSquaredConstant()
{
var mse = new Mse(5);
for (int i = 0; i < 10; i++)
{
mse.Update(100, 110); // Constant error of 10, squared = 100
}
Assert.Equal(100.0, mse.Last.Value, 10);
}
[Fact]
public void Mse_PenalizesLargeErrors()
{
var mse = new Mse(3);
// Small errors: (1-2)² = 1, (2-3)² = 1, (3-4)² = 1
// Mean = 1
mse.Update(1, 2);
mse.Update(2, 3);
var smallResult = mse.Update(3, 4);
Assert.Equal(1.0, smallResult.Value, 10);
mse.Reset();
// Large error: (1-11)² = 100, (2-3)² = 1, (3-4)² = 1
// Mean = 102/3 = 34
mse.Update(1, 11); // Large error
mse.Update(2, 3);
var largeResult = mse.Update(3, 4);
Assert.Equal(102.0 / 3.0, largeResult.Value, 10);
}
[Fact]
public void Calc_IsNew_AcceptsParameter()
{
var mse = new Mse(10);
mse.Update(100, 110, isNew: true);
double value1 = mse.Last.Value;
mse.Update(100, 120, isNew: true);
double value2 = mse.Last.Value;
Assert.NotEqual(value1, value2);
}
[Fact]
public void Calc_IsNew_False_UpdatesValue()
{
var mse = new Mse(10);
mse.Update(100, 110);
mse.Update(100, 120, isNew: true);
double beforeUpdate = mse.Last.Value;
mse.Update(100, 130, isNew: false);
double afterUpdate = mse.Last.Value;
Assert.NotEqual(beforeUpdate, afterUpdate);
}
[Fact]
public void IterativeCorrections_RestoreToOriginalState()
{
var mse = new Mse(5);
double tenthActual = 0;
double tenthPredicted = 0;
// Feed 10 updates
for (int i = 0; i < 10; i++)
{
tenthActual = i * 10;
tenthPredicted = i * 10 + 5;
mse.Update(tenthActual, tenthPredicted);
}
double stateAfterTen = mse.Last.Value;
// Apply 5 corrections with isNew=false
for (int i = 0; i < 5; i++)
{
mse.Update(100 + i, 200 + i, isNew: false);
}
// Restore to original values
mse.Update(tenthActual, tenthPredicted, isNew: false);
Assert.Equal(stateAfterTen, mse.Last.Value, 10);
}
[Fact]
public void Reset_ClearsState()
{
var mse = new Mse(5);
for (int i = 0; i < 10; i++)
{
mse.Update(i * 10, i * 10 + 5);
}
Assert.True(mse.IsHot);
mse.Reset();
Assert.False(mse.IsHot);
Assert.Equal(0, mse.Last.Value);
}
[Fact]
public void NaN_Input_UsesLastValidValue()
{
var mse = new Mse(5);
mse.Update(100, 110);
mse.Update(110, 120);
mse.Update(120, 130);
var result = mse.Update(double.NaN, double.NaN);
Assert.True(double.IsFinite(result.Value));
}
[Fact]
public void Infinity_Input_UsesLastValidValue()
{
var mse = new Mse(5);
mse.Update(100, 110);
mse.Update(110, 120);
var result = mse.Update(double.PositiveInfinity, double.NegativeInfinity);
Assert.True(double.IsFinite(result.Value));
}
[Fact]
public void Mse_Throws_On_Single_Input()
{
var mse = new Mse(10);
Assert.Throws<NotSupportedException>(() => mse.Update(new TValue(DateTime.UtcNow, 1)));
Assert.Throws<NotSupportedException>(() => mse.Update(new TSeries()));
Assert.Throws<NotSupportedException>(() => mse.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 mse = new Mse(period);
var streamingResults = new double[count];
for (int i = 0; i < count; i++)
{
streamingResults[i] = mse.Update(actual[i], predicted[i]).Value;
}
// Batch
double[] batchResults = new double[count];
Mse.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 = [1, 2, 3, 4, 5];
double[] predicted = [1, 2, 3, 4, 5];
double[] output = new double[5];
Assert.Throws<ArgumentException>(() =>
Mse.Batch(actual.AsSpan(), predicted.AsSpan(), output.AsSpan(), 0));
Assert.Throws<ArgumentException>(() =>
Mse.Batch(actual.AsSpan(), predicted.AsSpan(), output.AsSpan(), -1));
Assert.Throws<ArgumentException>(() =>
Mse.Batch(actual.AsSpan(), predicted.AsSpan(), new double[3].AsSpan(), 3));
}
[Fact]
public void Calculate_Works()
{
var actual = new TSeries();
var predicted = new TSeries();
var now = DateTime.UtcNow;
for (int i = 0; i < 10; i++)
{
actual.Add(now.AddMinutes(i), i * 10);
predicted.Add(now.AddMinutes(i), i * 10 + 5);
}
var results = Mse.Batch(actual, predicted, 3);
Assert.Equal(10, results.Count);
// All errors are 5², so MSE should be 25
Assert.Equal(25.0, results.Last.Value, 10);
}
[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];
Mse.Batch(actual, predicted, output, 3);
foreach (var val in output)
{
Assert.True(double.IsFinite(val), $"Expected finite value but got {val}");
}
}
}