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QuanTAlib/lib/errors/me/tests/Me.Tests.cs
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Miha Kralj 060649192f docs: remove C# Implementation Considerations sections, clean up temp scripts, reorganize test files
- Remove 'C# Implementation Considerations' sections from 34 indicator .md files
- Delete 29 temp PowerShell scripts (_fix_mojibake.ps1, _hex_scan.ps1, etc.)
- Move test files into tests/ subdirectories for consistent project structure
- Add trader-focused bullet points to indicator documentation
2026-03-12 12:34:16 -07:00

462 lines
12 KiB
C#

namespace QuanTAlib.Tests;
public class MeTests
{
[Fact]
public void Constructor_ValidatesInput()
{
Assert.Throws<ArgumentException>(() => new Me(0));
Assert.Throws<ArgumentException>(() => new Me(-1));
var me = new Me(10);
Assert.NotNull(me);
}
[Fact]
public void Properties_Accessible()
{
var me = new Me(10);
Assert.Equal(0, me.Last.Value);
Assert.False(me.IsHot);
Assert.Contains("Me", me.Name, StringComparison.Ordinal);
me.Update(100, 105);
Assert.NotEqual(0, me.Last.Value);
}
[Fact]
public void IsHot_BecomesTrueWhenBufferFull()
{
const int period = 5;
var me = new Me(period);
for (int i = 0; i < period - 1; i++)
{
Assert.False(me.IsHot, $"IsHot should be false at index {i}");
me.Update(i * 10, i * 10 + 5);
}
me.Update((period - 1) * 10, (period - 1) * 10 + 5);
Assert.True(me.IsHot, "IsHot should be true after period updates");
}
[Fact]
public void Me_CalculatesCorrectly()
{
var me = new Me(3);
// 10 - 15 = -5
var res1 = me.Update(10, 15);
Assert.Equal(-5.0, res1.Value, 10);
// 20 - 30 = -10, Mean = (-5 + -10) / 2 = -7.5
var res2 = me.Update(20, 30);
Assert.Equal(-7.5, res2.Value, 10);
// 30 - 25 = 5, Mean = (-5 + -10 + 5) / 3 = -10/3
var res3 = me.Update(30, 25);
Assert.Equal(-10.0 / 3.0, res3.Value, 10);
// 40 - 35 = 5, Window slides: (-10 + 5 + 5) / 3 = 0
var res4 = me.Update(40, 35);
Assert.Equal(0.0, res4.Value, 10);
}
[Fact]
public void Me_PerfectPrediction_ReturnsZero()
{
var me = new Me(5);
for (int i = 0; i < 10; i++)
{
me.Update(i * 10, i * 10); // Perfect prediction
}
Assert.Equal(0.0, me.Last.Value, 10);
}
[Fact]
public void Me_ConstantUnderPrediction_ReturnsPositive()
{
var me = new Me(5);
for (int i = 0; i < 10; i++)
{
me.Update(110, 100); // Actual > predicted (under-prediction)
}
Assert.Equal(10.0, me.Last.Value, 10);
}
[Fact]
public void Me_ConstantOverPrediction_ReturnsNegative()
{
var me = new Me(5);
for (int i = 0; i < 10; i++)
{
me.Update(100, 110); // Actual < predicted (over-prediction)
}
Assert.Equal(-10.0, me.Last.Value, 10);
}
[Fact]
public void Me_BalancedErrors_CancelOut()
{
var me = new Me(4);
// Errors: +10, -10, +10, -10 should cancel out
me.Update(110, 100); // +10
me.Update(90, 100); // -10
me.Update(110, 100); // +10
me.Update(90, 100); // -10
Assert.Equal(0.0, me.Last.Value, 10);
}
[Fact]
public void Me_PreservesSign()
{
var me = new Me(3);
// Error = 15 - 10 = 5 (under-prediction)
me.Update(15, 10);
Assert.True(me.Last.Value > 0, "ME should be positive for under-prediction");
var me2 = new Me(3);
// Error = 10 - 15 = -5 (over-prediction)
me2.Update(10, 15);
Assert.True(me2.Last.Value < 0, "ME should be negative for over-prediction");
}
[Fact]
public void Calc_IsNew_AcceptsParameter()
{
var me = new Me(10);
me.Update(100, 110, isNew: true);
double value1 = me.Last.Value;
me.Update(100, 120, isNew: true);
double value2 = me.Last.Value;
Assert.NotEqual(value1, value2);
}
[Fact]
public void Calc_IsNew_False_UpdatesValue()
{
var me = new Me(10);
me.Update(100, 110);
me.Update(100, 120, isNew: true);
double beforeUpdate = me.Last.Value;
me.Update(100, 130, isNew: false);
double afterUpdate = me.Last.Value;
Assert.NotEqual(beforeUpdate, afterUpdate);
}
[Fact]
public void IterativeCorrections_RestoreToOriginalState()
{
var me = new Me(5);
double tenthActual = 0;
double tenthPredicted = 0;
// Feed 10 updates
for (int i = 0; i < 10; i++)
{
tenthActual = i * 10;
tenthPredicted = i * 10 + 5;
me.Update(tenthActual, tenthPredicted);
}
double stateAfterTen = me.Last.Value;
// Apply 5 corrections with isNew=false
for (int i = 0; i < 5; i++)
{
me.Update(100 + i, 200 + i, isNew: false);
}
// Restore to original values
me.Update(tenthActual, tenthPredicted, isNew: false);
Assert.Equal(stateAfterTen, me.Last.Value, 10);
}
[Fact]
public void Reset_ClearsState()
{
var me = new Me(5);
for (int i = 0; i < 10; i++)
{
me.Update(i * 10, i * 10 + 5);
}
Assert.True(me.IsHot);
me.Reset();
Assert.False(me.IsHot);
Assert.Equal(0, me.Last.Value);
}
[Fact]
public void NaN_Input_UsesLastValidValue()
{
var me = new Me(5);
me.Update(100, 110);
me.Update(110, 120);
me.Update(120, 130);
var result = me.Update(double.NaN, double.NaN);
Assert.True(double.IsFinite(result.Value));
}
[Fact]
public void Infinity_Input_UsesLastValidValue()
{
var me = new Me(5);
me.Update(100, 110);
me.Update(110, 120);
var result = me.Update(double.PositiveInfinity, double.NegativeInfinity);
Assert.True(double.IsFinite(result.Value));
}
[Fact]
public void MultipleNaN_ContinuesWithLastValid()
{
var me = new Me(5);
me.Update(100, 110);
me.Update(110, 120);
me.Update(120, 130);
var r1 = me.Update(double.NaN, double.NaN);
var r2 = me.Update(double.NaN, double.NaN);
var r3 = me.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 Me_Throws_On_Single_Input()
{
var me = new Me(10);
Assert.Throws<NotSupportedException>(() => me.Update(new TValue(DateTime.UtcNow, 1)));
Assert.Throws<NotSupportedException>(() => me.Update(new TSeries()));
Assert.Throws<NotSupportedException>(() => me.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; // Offset prediction
}
// Streaming
var me = new Me(period);
var streamingResults = new double[count];
for (int i = 0; i < count; i++)
{
streamingResults[i] = me.Update(actual[i], predicted[i]).Value;
}
// Batch
double[] batchResults = new double[count];
Me.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];
double[] wrongSizeOutput = new double[3];
double[] wrongSizePredicted = new double[3];
// Period must be > 0
Assert.Throws<ArgumentException>(() =>
Me.Batch(actual.AsSpan(), predicted.AsSpan(), output.AsSpan(), 0));
Assert.Throws<ArgumentException>(() =>
Me.Batch(actual.AsSpan(), predicted.AsSpan(), output.AsSpan(), -1));
// Output must be same length as source
Assert.Throws<ArgumentException>(() =>
Me.Batch(actual.AsSpan(), predicted.AsSpan(), wrongSizeOutput.AsSpan(), 3));
// Predicted must be same length as actual
Assert.Throws<ArgumentException>(() =>
Me.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 = 0; i < 10; i++)
{
actual.Add(now.AddMinutes(i), i * 10);
predicted.Add(now.AddMinutes(i), i * 10 + 5);
}
var results = Me.Batch(actual, predicted, 3);
Assert.Equal(10, results.Count);
// All errors are -5, so ME should be -5
Assert.Equal(-5.0, results.Last.Value, 10);
}
[Fact]
public void Calculate_ValidatesMismatchedLengths()
{
var actual = new TSeries();
var predicted = new TSeries();
for (int i = 0; i < 10; i++)
{
actual.Add(DateTime.UtcNow, i);
}
for (int i = 0; i < 5; i++)
{
predicted.Add(DateTime.UtcNow, i);
}
Assert.Throws<ArgumentException>(() => Me.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];
Me.Batch(actual, predicted, output, 3);
foreach (var val in output)
{
Assert.True(double.IsFinite(val), $"Expected finite value but got {val}");
}
}
[Fact]
public void Me_Resync_Works()
{
var me = new Me(5);
// Force many updates to trigger resync (ResyncInterval = 1000)
for (int i = 0; i < 1100; i++)
{
me.Update(110, 100); // Constant error of +10
}
// After resync, result should still be correct
Assert.Equal(10.0, me.Last.Value, 10);
}
[Fact]
public void BatchSpan_EmptyInput_ReturnsWithoutChanges()
{
double[] actual = [];
double[] predicted = [];
double[] output = [];
Me.Batch(actual.AsSpan(), predicted.AsSpan(), output.AsSpan(), 3);
Assert.Empty(output);
}
[Fact]
public void BatchSpan_LargeInput_MatchesStreaming()
{
const int period = 9;
const int count = 300; // exceeds stack-alloc threshold branch
var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 321);
var me = new Me(period);
double[] actual = new double[count];
double[] predicted = new double[count];
double[] streaming = new double[count];
double[] batch = new double[count];
for (int i = 0; i < count; i++)
{
var bar = gbm.Next();
actual[i] = bar.Close;
predicted[i] = bar.Close * (1 + (i % 2 == 0 ? 0.01 : -0.015));
streaming[i] = me.Update(actual[i], predicted[i]).Value;
}
Me.Batch(actual.AsSpan(), predicted.AsSpan(), batch.AsSpan(), period);
for (int i = 0; i < count; i++)
{
Assert.Equal(streaming[i], batch[i], 9);
}
}
[Fact]
public void Calculate_ReturnsConfiguredIndicatorAndMatchingResults()
{
const int period = 6;
var actual = new TSeries();
var predicted = new TSeries();
var now = DateTime.UtcNow;
for (int i = 0; i < 40; i++)
{
actual.Add(now.AddSeconds(i), 100 + i);
predicted.Add(now.AddSeconds(i), 101 + i);
}
var (results, indicator) = Me.Calculate(actual, predicted, period);
var batch = Me.Batch(actual, predicted, period);
Assert.NotNull(indicator);
Assert.Equal(period, indicator.WarmupPeriod);
Assert.Equal(batch.Count, results.Count);
for (int i = 0; i < results.Count; i++)
{
Assert.Equal(batch[i].Value, results[i].Value, 10);
}
}
}