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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
This commit is contained in:
Miha Kralj
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namespace QuanTAlib.Tests;
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public class RmseTests
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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 Rmse(0));
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Assert.Throws<ArgumentException>(() => new Rmse(-1));
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var rmse = new Rmse(10);
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Assert.NotNull(rmse);
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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 rmse = new Rmse(10);
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Assert.Equal(0, rmse.Last.Value);
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Assert.False(rmse.IsHot);
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Assert.Contains("Rmse", rmse.Name, StringComparison.Ordinal);
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rmse.Update(100, 105);
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Assert.NotEqual(0, rmse.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 rmse = new Rmse(period);
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for (int i = 0; i < period - 1; i++)
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{
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Assert.False(rmse.IsHot);
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rmse.Update(i * 10, i * 10 + 5);
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}
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rmse.Update((period - 1) * 10, (period - 1) * 10 + 5);
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Assert.True(rmse.IsHot);
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}
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[Fact]
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public void Rmse_CalculatesCorrectly()
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{
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var rmse = new Rmse(3);
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// (10 - 15)² = 25, RMSE = √25 = 5
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var res1 = rmse.Update(10, 15);
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Assert.Equal(5.0, res1.Value, 10);
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// (20 - 30)² = 100, MSE = (25 + 100) / 2 = 62.5, RMSE = √62.5
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var res2 = rmse.Update(20, 30);
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Assert.Equal(Math.Sqrt(62.5), res2.Value, 10);
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// (30 - 25)² = 25, MSE = (25 + 100 + 25) / 3 = 50, RMSE = √50
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var res3 = rmse.Update(30, 25);
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Assert.Equal(Math.Sqrt(50.0), res3.Value, 10);
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}
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[Fact]
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public void Rmse_IsSqrtOfMse()
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{
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var rmse = new Rmse(5);
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var mse = new Mse(5);
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for (int i = 0; i < 20; i++)
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{
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rmse.Update(i * 10, i * 10 + 7);
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mse.Update(i * 10, i * 10 + 7);
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}
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Assert.Equal(Math.Sqrt(mse.Last.Value), rmse.Last.Value, 10);
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}
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[Fact]
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public void Rmse_PerfectPrediction_ReturnsZero()
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{
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var rmse = new Rmse(5);
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for (int i = 0; i < 10; i++)
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{
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rmse.Update(i * 10, i * 10);
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}
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Assert.Equal(0.0, rmse.Last.Value, 10);
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}
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[Fact]
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public void Rmse_ConstantError_ReturnsSameAsError()
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{
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var rmse = new Rmse(5);
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for (int i = 0; i < 10; i++)
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{
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rmse.Update(100, 110); // Constant error of 10
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}
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// MSE = 100, RMSE = √100 = 10 (same as error because error is constant)
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Assert.Equal(10.0, rmse.Last.Value, 10);
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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 rmse = new Rmse(10);
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rmse.Update(100, 110);
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rmse.Update(100, 120, isNew: true);
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double beforeUpdate = rmse.Last.Value;
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rmse.Update(100, 130, isNew: false);
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double afterUpdate = rmse.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 rmse = new Rmse(5);
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double tenthActual = 0;
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double tenthPredicted = 0;
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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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rmse.Update(tenthActual, tenthPredicted);
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}
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double stateAfterTen = rmse.Last.Value;
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for (int i = 0; i < 5; i++)
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{
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rmse.Update(100 + i, 200 + i, isNew: false);
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}
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rmse.Update(tenthActual, tenthPredicted, isNew: false);
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Assert.Equal(stateAfterTen, rmse.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 rmse = new Rmse(5);
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for (int i = 0; i < 10; i++)
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{
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rmse.Update(i * 10, i * 10 + 5);
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}
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Assert.True(rmse.IsHot);
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rmse.Reset();
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Assert.False(rmse.IsHot);
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Assert.Equal(0, rmse.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 rmse = new Rmse(5);
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rmse.Update(100, 110);
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rmse.Update(110, 120);
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var result = rmse.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 Rmse_Throws_On_Single_Input()
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{
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var rmse = new Rmse(10);
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Assert.Throws<NotSupportedException>(() => rmse.Update(new TValue(DateTime.UtcNow, 1)));
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Assert.Throws<NotSupportedException>(() => rmse.Update(new TSeries()));
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Assert.Throws<NotSupportedException>(() => rmse.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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var rmse = new Rmse(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] = rmse.Update(actual[i], predicted[i]).Value;
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}
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double[] batchResults = new double[count];
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Rmse.Batch(actual, predicted, batchResults, period);
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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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Rmse.Batch(actual.AsSpan(), predicted.AsSpan(), output.AsSpan(), 0));
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Assert.Throws<ArgumentException>(() =>
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Rmse.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 = Rmse.Batch(actual, predicted, 3);
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Assert.Equal(10, results.Count);
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// All errors are 5, MSE = 25, RMSE = 5
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Assert.Equal(5.0, results.Last.Value, 10);
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}
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}
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@@ -0,0 +1,102 @@
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using MathNet.Numerics;
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using QuanTAlib.Tests;
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namespace QuanTAlib.Validation;
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public sealed class RmseValidationTests : IDisposable
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{
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private readonly ValidationTestData _data = new();
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public void Dispose() => _data.Dispose();
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[Fact]
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public void Rmse_Matches_MathNet()
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{
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int[] periods = { 5, 10, 20, 50, 100 };
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var quotes = _data.SkenderQuotes.ToList();
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double[] actual = quotes.Select(q => (double)q.Close).ToArray();
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double[] predicted = quotes.Select(q => (double)q.Open).ToArray();
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foreach (int period in periods)
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{
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var rmse = new Rmse(period);
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for (int i = 0; i < actual.Length; i++)
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{
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var val = rmse.Update(
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new TValue(quotes[i].Date, actual[i]),
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new TValue(quotes[i].Date, predicted[i]));
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// Validate last 100 bars
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if (i >= actual.Length - 100 && i >= period - 1)
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{
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var windowActual = actual[(i - period + 1)..(i + 1)];
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var windowPredicted = predicted[(i - period + 1)..(i + 1)];
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// RMSE = sqrt(MSE)
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double expected = Math.Sqrt(Distance.MSE(windowActual, windowPredicted));
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Assert.Equal(expected, val.Value, 1e-9);
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}
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}
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}
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}
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[Fact]
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public void Rmse_Batch_Matches_MathNet()
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{
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int[] periods = { 5, 10, 20, 50, 100 };
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var quotes = _data.SkenderQuotes.ToList();
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double[] actual = quotes.Select(q => (double)q.Close).ToArray();
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double[] predicted = quotes.Select(q => (double)q.Open).ToArray();
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foreach (int period in periods)
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{
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double[] output = new double[actual.Length];
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Rmse.Batch(actual, predicted, output, period);
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// Validate last 100 bars
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for (int i = actual.Length - 100; i < actual.Length; i++)
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{
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if (i >= period - 1)
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{
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var windowActual = actual[(i - period + 1)..(i + 1)];
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var windowPredicted = predicted[(i - period + 1)..(i + 1)];
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// RMSE = sqrt(MSE)
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double expected = Math.Sqrt(Distance.MSE(windowActual, windowPredicted));
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Assert.Equal(expected, output[i], 1e-9);
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}
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}
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}
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}
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[Fact]
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public void Rmse_Correction_Recomputes()
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{
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var ind = new Rmse(20);
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// Build state well past warmup
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for (int i = 0; i < 50; i++)
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{
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ind.Update(100.0 + (i * 0.5), 98.0 + (i * 0.5));
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}
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// Anchor bar
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const double anchorActual = 125.0;
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const double anchorPredicted = 123.0;
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ind.Update(anchorActual, anchorPredicted, isNew: true);
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double anchorResult = ind.Last.Value;
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// Correction with dramatically different values — recompute must yield different result
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ind.Update(anchorActual * 10, anchorPredicted * 10, isNew: false);
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Assert.NotEqual(anchorResult, ind.Last.Value);
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// Correction back to original — must exactly restore original result
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ind.Update(anchorActual, anchorPredicted, isNew: false);
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Assert.Equal(anchorResult, ind.Last.Value, 1e-9);
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}
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}
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