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
273 lines
8.2 KiB
C#
273 lines
8.2 KiB
C#
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namespace QuanTAlib.Tests;
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public class StdDevTests
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{
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[Fact]
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public void Constructor_ValidatesPeriod()
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{
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Assert.Throws<ArgumentOutOfRangeException>(() => new StdDev(1));
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Assert.Throws<ArgumentOutOfRangeException>(() => new StdDev(0));
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Assert.Throws<ArgumentOutOfRangeException>(() => new StdDev(-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 stddev = new StdDev(5);
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Assert.Equal(0, stddev.Last.Value);
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Assert.False(stddev.IsHot);
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Assert.Contains("StdDev", stddev.Name, StringComparison.Ordinal);
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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 stddev = new StdDev(3);
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stddev.Update(new TValue(DateTime.UtcNow, 10));
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stddev.Update(new TValue(DateTime.UtcNow, 20));
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stddev.Update(new TValue(DateTime.UtcNow, 30));
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double valueBefore = stddev.Last.Value;
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// Update with isNew=false should change the result
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stddev.Update(new TValue(DateTime.UtcNow, 100), isNew: false);
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double valueAfter = stddev.Last.Value;
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Assert.NotEqual(valueBefore, valueAfter);
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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 stddev = new StdDev(5);
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stddev.Update(new TValue(DateTime.UtcNow, 10));
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stddev.Update(new TValue(DateTime.UtcNow, 20));
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var result = stddev.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 stddev = new StdDev(5);
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stddev.Update(new TValue(DateTime.UtcNow, 10));
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stddev.Update(new TValue(DateTime.UtcNow, 20));
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var resultPosInf = stddev.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
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Assert.True(double.IsFinite(resultPosInf.Value));
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var resultNegInf = stddev.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 stddev = new StdDev(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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stddev.Update(tenthInput, isNew: true);
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}
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// Remember state after 10 values
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double stateAfterTen = stddev.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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stddev.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 = stddev.Update(tenthInput, isNew: false);
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// State should match the original state after 10 values
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// Note: FMA optimization in RingBuffer provides better precision, so we use a slightly relaxed tolerance
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Assert.Equal(stateAfterTen, finalResult.Value, 1e-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 > 1
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Assert.Throws<ArgumentException>(() =>
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StdDev.Batch(source.AsSpan(), output.AsSpan(), 1));
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// Output must be same length as source
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Assert.Throws<ArgumentException>(() =>
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StdDev.Batch(source.AsSpan(), wrongSizeOutput.AsSpan(), 3));
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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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const int period = 10;
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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 (static span)
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var tValues = series.Values.ToArray();
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var batchOutput = new double[tValues.Length];
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StdDev.Batch(tValues, batchOutput, period);
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double expected = batchOutput[^1];
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// 2. Streaming Mode
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var streamingInd = new StdDev(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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// 3. TSeries Batch Mode
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var batchSeriesResult = StdDev.Batch(series, period);
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double tseriesResult = batchSeriesResult.Last.Value;
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Assert.Equal(expected, streamingResult, precision: 6);
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Assert.Equal(expected, tseriesResult, precision: 6);
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}
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[Fact]
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public void Calculation_KnownValues()
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{
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// Data: 2, 4, 4, 4, 5, 5, 7, 9
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// Mean: 5
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// Deviations: -3, -1, -1, -1, 0, 0, 2, 4
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// Sq Devs: 9, 1, 1, 1, 0, 0, 4, 16
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// Sum Sq Devs: 32
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// Population Variance (N=8): 32 / 8 = 4
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// Population StdDev: Sqrt(4) = 2
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// Sample Variance (N-1=7): 32 / 7 = 4.571428...
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// Sample StdDev: Sqrt(4.571428...) = 2.1380899...
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double[] data = [2, 4, 4, 4, 5, 5, 7, 9];
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// Test Population StdDev
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var popStd = new StdDev(8, isPopulation: true);
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foreach (var val in data)
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{
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popStd.Update(new TValue(DateTime.UtcNow, val));
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}
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Assert.Equal(2.0, popStd.Last.Value, precision: 6);
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// Test Sample StdDev
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var sampStd = new StdDev(8, isPopulation: false);
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foreach (var val in data)
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{
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sampStd.Update(new TValue(DateTime.UtcNow, val));
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}
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Assert.Equal(Math.Sqrt(32.0 / 7.0), sampStd.Last.Value, precision: 6);
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}
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[Fact]
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public void IsHot_BecomesTrueAfterPeriod()
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{
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const int period = 5;
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var stdDev = new StdDev(period);
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for (int i = 0; i < period; i++)
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{
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Assert.False(stdDev.IsHot);
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stdDev.Update(new TValue(DateTime.UtcNow, i));
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}
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Assert.True(stdDev.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 stdDev = new StdDev(5);
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for (int i = 0; i < 10; i++)
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{
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stdDev.Update(new TValue(DateTime.UtcNow, i));
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}
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Assert.True(stdDev.IsHot);
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stdDev.Reset();
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Assert.False(stdDev.IsHot);
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Assert.Equal(0, stdDev.Last.Value);
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}
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[Fact]
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public void Batch_Matches_Iterative()
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{
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int period = 10;
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int count = 1000;
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var data = new double[count];
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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 < count; i++)
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{
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data[i] = gbm.Next().Close;
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}
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// Iterative
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var stdDev = new StdDev(period);
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var iterativeResults = new double[count];
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for (int i = 0; i < count; i++)
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{
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stdDev.Update(new TValue(DateTime.UtcNow, data[i]));
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iterativeResults[i] = stdDev.Last.Value;
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}
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// Batch
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var batchResults = new double[count];
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StdDev.Batch(data, 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(iterativeResults[i], batchResults[i], precision: 6);
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}
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}
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[Fact]
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public void Update_TSeries_Matches_Iterative()
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{
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int period = 10;
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int count = 1000;
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var data = 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 < count; i++)
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{
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var bar = gbm.Next();
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data.Add(new TValue(bar.Time, bar.Close));
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}
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// Iterative
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var stdDev = new StdDev(period);
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var iterativeResults = new double[count];
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for (int i = 0; i < count; i++)
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{
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stdDev.Update(data[i]);
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iterativeResults[i] = stdDev.Last.Value;
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}
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// TSeries Batch
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var stdDevBatch = new StdDev(period);
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var batchSeries = stdDevBatch.Update(data);
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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(iterativeResults[i], batchSeries[i].Value, precision: 6);
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}
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}
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}
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