mirror of
https://github.com/mihakralj/QuanTAlib.git
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060649192f
- 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
291 lines
8.6 KiB
C#
291 lines
8.6 KiB
C#
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namespace QuanTAlib;
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public class MedianTests
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{
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[Fact]
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public void Constructor_ValidatesInput()
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{
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Assert.Throws<ArgumentException>(() => new Median(0));
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Assert.Throws<ArgumentException>(() => new Median(-1));
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}
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[Fact]
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public void Properties_Accessible()
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{
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var median = new Median(5);
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Assert.Equal(0, median.Last.Value);
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Assert.False(median.IsHot);
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Assert.Contains("Median", median.Name, StringComparison.Ordinal);
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}
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[Fact]
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public void IsHot_BecomesTrueWhenBufferFull()
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{
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var median = new Median(5);
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Assert.False(median.IsHot);
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for (int i = 1; i <= 4; i++)
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{
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median.Update(new TValue(DateTime.UtcNow, i * 10));
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Assert.False(median.IsHot);
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}
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median.Update(new TValue(DateTime.UtcNow, 50));
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Assert.True(median.IsHot);
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}
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[Fact]
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public void Reset_ClearsState()
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{
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var median = new Median(5);
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for (int i = 0; i < 10; i++)
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{
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median.Update(new TValue(DateTime.UtcNow, i * 10));
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}
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Assert.True(median.IsHot);
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median.Reset();
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Assert.False(median.IsHot);
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Assert.Equal(0, median.Last.Value);
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// After reset, should accept new values
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var result = median.Update(new TValue(DateTime.UtcNow, 50));
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Assert.Equal(50, result.Value);
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}
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[Fact]
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public void NaN_Input_UsesLastValidValue()
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{
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var median = new Median(3);
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median.Update(new TValue(DateTime.UtcNow, 10));
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median.Update(new TValue(DateTime.UtcNow, 20));
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var result = median.Update(new TValue(DateTime.UtcNow, double.NaN));
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Assert.True(double.IsFinite(result.Value));
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}
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[Fact]
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public void Infinity_Input_UsesLastValidValue()
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{
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var median = new Median(3);
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median.Update(new TValue(DateTime.UtcNow, 10));
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median.Update(new TValue(DateTime.UtcNow, 20));
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var resultPosInf = median.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
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Assert.True(double.IsFinite(resultPosInf.Value));
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var resultNegInf = median.Update(new TValue(DateTime.UtcNow, double.NegativeInfinity));
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Assert.True(double.IsFinite(resultNegInf.Value));
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}
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[Fact]
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public void IterativeCorrections_RestoreToOriginalState()
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{
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var median = new Median(5);
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
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// Feed 10 new values
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TValue tenthInput = default;
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for (int i = 0; i < 10; i++)
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{
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var bar = gbm.Next(isNew: true);
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tenthInput = new TValue(bar.Time, bar.Close);
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median.Update(tenthInput, isNew: true);
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}
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// Remember state after 10 values
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double stateAfterTen = median.Last.Value;
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// Generate 9 corrections with isNew=false (different values)
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for (int i = 0; i < 9; i++)
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{
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var bar = gbm.Next(isNew: false);
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median.Update(new TValue(bar.Time, bar.Close), isNew: false);
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}
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// Feed the remembered 10th input again with isNew=false
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TValue finalResult = median.Update(tenthInput, isNew: false);
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// State should match the original state after 10 values
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Assert.Equal(stateAfterTen, finalResult.Value, 1e-10);
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}
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[Fact]
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public void Median_OddPeriod_ReturnsMiddleValue()
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{
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// Arrange
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var median = new Median(3);
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// Act
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median.Update(new TValue(DateTime.MinValue, 10));
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median.Update(new TValue(DateTime.MinValue, 30));
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var result = median.Update(new TValue(DateTime.MinValue, 20));
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// Assert
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// Window: [10, 30, 20] -> Sorted: [10, 20, 30] -> Median: 20
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Assert.Equal(20, result.Value);
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}
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[Fact]
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public void Median_EvenPeriod_ReturnsAverageOfMiddleValues()
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{
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// Arrange
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var median = new Median(4);
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// Act
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median.Update(new TValue(DateTime.MinValue, 10));
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median.Update(new TValue(DateTime.MinValue, 40));
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median.Update(new TValue(DateTime.MinValue, 20));
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var result = median.Update(new TValue(DateTime.MinValue, 30));
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// Assert
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// Window: [10, 40, 20, 30] -> Sorted: [10, 20, 30, 40] -> Median: (20 + 30) / 2 = 25
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Assert.Equal(25, result.Value);
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}
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[Fact]
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public void Median_UpdatesWithIsNewFalse_Correctly()
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{
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// Arrange
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var median = new Median(3);
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// Act
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median.Update(new TValue(DateTime.MinValue, 10));
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median.Update(new TValue(DateTime.MinValue, 20));
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// Update with 30 (isNew=true)
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var r1 = median.Update(new TValue(DateTime.MinValue, 30));
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// Window: [10, 20, 30] -> Median 20
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Assert.Equal(20, r1.Value);
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// Update with 40 (isNew=false) -> Replaces 30 with 40
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var r2 = median.Update(new TValue(DateTime.MinValue, 40), isNew: false);
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// Window: [10, 20, 40] -> Median 20
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Assert.Equal(20, r2.Value);
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// Update with 5 (isNew=false) -> Replaces 40 with 5
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var r3 = median.Update(new TValue(DateTime.MinValue, 5), isNew: false);
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// Window: [10, 20, 5] -> Sorted [5, 10, 20] -> Median 10
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Assert.Equal(10, r3.Value);
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}
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[Fact]
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public void Median_Batch_Matches_Streaming()
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{
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// Arrange
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const int period = 5;
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var source = new TSeries();
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 123);
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for (int i = 0; i < 100; i++)
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{
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var bar = gbm.Next(isNew: true);
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source.Add(new TValue(bar.Time, bar.Close));
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}
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// Act
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var medianBatch = Median.Batch(source, period);
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var medianStream = new Median(period);
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var streamResults = new List<double>();
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foreach (var val in source)
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{
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streamResults.Add(medianStream.Update(val).Value);
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}
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// Assert
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for (int i = 0; i < source.Count; i++)
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{
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Assert.Equal(medianBatch.Values[i], streamResults[i], 1e-9);
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}
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}
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[Fact]
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public void AllModes_ProduceSameResult()
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{
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int period = 5;
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 123);
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var bars = gbm.Fetch(1000, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var series = bars.Close;
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// 1. Batch Mode
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var batchSeries = Median.Batch(series, period);
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double expected = batchSeries.Last.Value;
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// 2. Span Mode
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var tValues = series.Values.ToArray();
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var spanInput = new ReadOnlySpan<double>(tValues);
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var spanOutput = new double[tValues.Length];
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Median.Batch(spanInput, spanOutput, period);
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double spanResult = spanOutput[^1];
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// 3. Streaming Mode
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var streamingInd = new Median(period);
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for (int i = 0; i < series.Count; i++)
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{
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streamingInd.Update(series[i]);
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}
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double streamingResult = streamingInd.Last.Value;
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// 4. Eventing Mode
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var pubSource = new TSeries();
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var eventingInd = new Median(pubSource, period);
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for (int i = 0; i < series.Count; i++)
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{
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pubSource.Add(series[i]);
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}
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double eventingResult = eventingInd.Last.Value;
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Assert.Equal(expected, spanResult, precision: 9);
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Assert.Equal(expected, streamingResult, precision: 9);
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Assert.Equal(expected, eventingResult, precision: 9);
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}
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[Fact]
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public void SpanBatch_ValidatesInput()
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{
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double[] source = [1, 2, 3, 4, 5];
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double[] output = new double[5];
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double[] wrongSizeOutput = new double[3];
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// Period must be > 0
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Assert.Throws<ArgumentException>(() =>
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Median.Batch(source.AsSpan(), output.AsSpan(), 0));
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// Output must be same length as source
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Assert.Throws<ArgumentException>(() =>
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Median.Batch(source.AsSpan(), wrongSizeOutput.AsSpan(), 3));
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}
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[Fact]
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public void Median_StaticBatch_Matches_ClassBatch()
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{
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// Arrange
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int period = 5;
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double[] data = new double[20];
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for (int i = 0; i < data.Length; i++)
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{
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data[i] = i;
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}
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// Act
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double[] output = new double[data.Length];
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Median.Batch(data, output, period);
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var series = new TSeries();
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for (int i = 0; i < data.Length; i++)
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{
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series.Add(new TValue(DateTime.MinValue, data[i]));
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}
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var batchSeries = Median.Batch(series, period);
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// Assert
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for (int i = 0; i < data.Length; i++)
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{
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Assert.Equal(batchSeries.Values[i], output[i], 1e-9);
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}
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}
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}
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