mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-29 02:07:42 +00:00
312 lines
8.0 KiB
C#
312 lines
8.0 KiB
C#
namespace QuanTAlib.Tests;
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public class MseTests
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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 Mse(0));
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Assert.Throws<ArgumentException>(() => new Mse(-1));
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var mse = new Mse(10);
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Assert.NotNull(mse);
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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 mse = new Mse(10);
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Assert.Equal(0, mse.Last.Value);
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Assert.False(mse.IsHot);
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Assert.Contains("Mse", mse.Name, StringComparison.Ordinal);
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mse.Update(100, 105);
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Assert.NotEqual(0, mse.Last.Value);
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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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const int period = 5;
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var mse = new Mse(period);
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for (int i = 0; i < period - 1; i++)
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{
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Assert.False(mse.IsHot, $"IsHot should be false at index {i}");
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mse.Update(i * 10, i * 10 + 5);
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}
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mse.Update((period - 1) * 10, (period - 1) * 10 + 5);
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Assert.True(mse.IsHot, "IsHot should be true after period updates");
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}
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[Fact]
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public void Mse_CalculatesCorrectly()
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{
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var mse = new Mse(3);
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// (10 - 15)² = 25
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var res1 = mse.Update(10, 15);
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Assert.Equal(25.0, res1.Value, 10);
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// (20 - 30)² = 100, Mean = (25 + 100) / 2 = 62.5
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var res2 = mse.Update(20, 30);
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Assert.Equal(62.5, res2.Value, 10);
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// (30 - 25)² = 25, Mean = (25 + 100 + 25) / 3 = 50
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var res3 = mse.Update(30, 25);
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Assert.Equal(50.0, res3.Value, 10);
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// (40 - 35)² = 25, Window slides: (100 + 25 + 25) / 3 = 50
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var res4 = mse.Update(40, 35);
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Assert.Equal(50.0, res4.Value, 10);
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}
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[Fact]
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public void Mse_PerfectPrediction_ReturnsZero()
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{
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var mse = new Mse(5);
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for (int i = 0; i < 10; i++)
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{
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mse.Update(i * 10, i * 10); // Perfect prediction
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}
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Assert.Equal(0.0, mse.Last.Value, 10);
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}
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[Fact]
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public void Mse_ConstantError_ReturnsSquaredConstant()
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{
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var mse = new Mse(5);
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for (int i = 0; i < 10; i++)
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{
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mse.Update(100, 110); // Constant error of 10, squared = 100
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}
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Assert.Equal(100.0, mse.Last.Value, 10);
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}
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[Fact]
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public void Mse_PenalizesLargeErrors()
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{
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var mse = new Mse(3);
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// Small errors: (1-2)² = 1, (2-3)² = 1, (3-4)² = 1
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// Mean = 1
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mse.Update(1, 2);
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mse.Update(2, 3);
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var smallResult = mse.Update(3, 4);
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Assert.Equal(1.0, smallResult.Value, 10);
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mse.Reset();
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// Large error: (1-11)² = 100, (2-3)² = 1, (3-4)² = 1
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// Mean = 102/3 = 34
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mse.Update(1, 11); // Large error
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mse.Update(2, 3);
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var largeResult = mse.Update(3, 4);
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Assert.Equal(102.0 / 3.0, largeResult.Value, 10);
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}
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[Fact]
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public void Calc_IsNew_AcceptsParameter()
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{
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var mse = new Mse(10);
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mse.Update(100, 110, isNew: true);
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double value1 = mse.Last.Value;
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mse.Update(100, 120, isNew: true);
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double value2 = mse.Last.Value;
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Assert.NotEqual(value1, value2);
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}
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[Fact]
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public void Calc_IsNew_False_UpdatesValue()
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{
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var mse = new Mse(10);
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mse.Update(100, 110);
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mse.Update(100, 120, isNew: true);
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double beforeUpdate = mse.Last.Value;
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mse.Update(100, 130, isNew: false);
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double afterUpdate = mse.Last.Value;
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Assert.NotEqual(beforeUpdate, afterUpdate);
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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 mse = new Mse(5);
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double tenthActual = 0;
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double tenthPredicted = 0;
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// Feed 10 updates
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for (int i = 0; i < 10; i++)
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{
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tenthActual = i * 10;
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tenthPredicted = i * 10 + 5;
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mse.Update(tenthActual, tenthPredicted);
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}
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double stateAfterTen = mse.Last.Value;
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// Apply 5 corrections with isNew=false
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for (int i = 0; i < 5; i++)
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{
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mse.Update(100 + i, 200 + i, isNew: false);
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}
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// Restore to original values
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mse.Update(tenthActual, tenthPredicted, isNew: false);
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Assert.Equal(stateAfterTen, mse.Last.Value, 10);
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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 mse = new Mse(5);
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for (int i = 0; i < 10; i++)
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{
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mse.Update(i * 10, i * 10 + 5);
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}
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Assert.True(mse.IsHot);
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mse.Reset();
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Assert.False(mse.IsHot);
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Assert.Equal(0, mse.Last.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 mse = new Mse(5);
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mse.Update(100, 110);
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mse.Update(110, 120);
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mse.Update(120, 130);
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var result = mse.Update(double.NaN, 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 mse = new Mse(5);
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mse.Update(100, 110);
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mse.Update(110, 120);
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var result = mse.Update(double.PositiveInfinity, double.NegativeInfinity);
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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 Mse_Throws_On_Single_Input()
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{
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var mse = new Mse(10);
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Assert.Throws<NotSupportedException>(() => mse.Update(new TValue(DateTime.UtcNow, 1)));
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Assert.Throws<NotSupportedException>(() => mse.Update(new TSeries()));
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Assert.Throws<NotSupportedException>(() => mse.Prime([1, 2, 3]));
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}
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[Fact]
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public void BatchSpan_MatchesStreaming()
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{
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int period = 5;
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int count = 100;
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 123);
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double[] actual = new double[count];
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double[] predicted = new double[count];
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for (int i = 0; i < count; i++)
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{
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var bar = gbm.Next();
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actual[i] = bar.Close;
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predicted[i] = bar.Close * 1.05 + 2;
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}
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// Streaming
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var mse = new Mse(period);
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var streamingResults = new double[count];
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for (int i = 0; i < count; i++)
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{
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streamingResults[i] = mse.Update(actual[i], predicted[i]).Value;
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}
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// Batch
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double[] batchResults = new double[count];
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Mse.Batch(actual, predicted, batchResults, period);
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// Compare
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for (int i = 0; i < count; i++)
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{
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Assert.Equal(streamingResults[i], batchResults[i], 9);
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}
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}
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[Fact]
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public void BatchSpan_ValidatesInput()
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{
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double[] actual = [1, 2, 3, 4, 5];
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double[] predicted = [1, 2, 3, 4, 5];
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double[] output = new double[5];
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Assert.Throws<ArgumentException>(() =>
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Mse.Batch(actual.AsSpan(), predicted.AsSpan(), output.AsSpan(), 0));
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Assert.Throws<ArgumentException>(() =>
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Mse.Batch(actual.AsSpan(), predicted.AsSpan(), output.AsSpan(), -1));
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Assert.Throws<ArgumentException>(() =>
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Mse.Batch(actual.AsSpan(), predicted.AsSpan(), new double[3].AsSpan(), 3));
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}
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[Fact]
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public void Calculate_Works()
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{
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var actual = new TSeries();
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var predicted = new TSeries();
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var now = DateTime.UtcNow;
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for (int i = 0; i < 10; i++)
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{
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actual.Add(now.AddMinutes(i), i * 10);
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predicted.Add(now.AddMinutes(i), i * 10 + 5);
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}
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var results = Mse.Batch(actual, predicted, 3);
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Assert.Equal(10, results.Count);
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// All errors are 5², so MSE should be 25
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Assert.Equal(25.0, results.Last.Value, 10);
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}
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[Fact]
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public void BatchSpan_HandlesNaN()
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{
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double[] actual = [100, 110, double.NaN, 130, 140];
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double[] predicted = [105, 115, 125, double.NaN, 145];
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double[] output = new double[5];
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Mse.Batch(actual, predicted, output, 3);
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foreach (var val in output)
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{
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Assert.True(double.IsFinite(val), $"Expected finite value but got {val}");
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}
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}
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}
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