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- 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
143 lines
4.4 KiB
C#
143 lines
4.4 KiB
C#
namespace QuanTAlib.Tests;
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/// <summary>
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/// Validation tests for Accel using synthetic data with known mathematical results.
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/// </summary>
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public class AccelValidationTests
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{
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[Fact]
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public void QuadraticSequence_ProducesConstantAccel()
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{
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// Quadratic sequence: 0, 1, 4, 9, 16, 25 (x^2)
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// Accel = second difference = 2 (constant for quadratic)
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// f(n) = n², slope(n) = 2n-1, accel = 2
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double[] data = [0, 1, 4, 9, 16, 25];
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double[] expected = [0, 0, 2, 2, 2, 2]; // First two are warmup (0), rest are 2
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var accel = new Accel();
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for (int i = 0; i < data.Length; i++)
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{
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var result = accel.Update(new TValue(DateTime.UtcNow, data[i]));
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Assert.Equal(expected[i], result.Value, precision: 9);
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}
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}
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[Fact]
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public void LinearSequence_ProducesZeroAccel()
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{
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// Linear sequence: 0, 2, 4, 6, 8, 10 (slope = 2, accel = 0)
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double[] data = [0, 2, 4, 6, 8, 10];
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double[] expected = [0, 0, 0, 0, 0, 0];
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var accel = new Accel();
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for (int i = 0; i < data.Length; i++)
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{
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var result = accel.Update(new TValue(DateTime.UtcNow, data[i]));
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Assert.Equal(expected[i], result.Value, precision: 9);
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}
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}
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[Fact]
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public void ConstantSequence_ProducesZeroAccel()
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{
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// Constant sequence: 5, 5, 5, 5, 5 (slope = 0, accel = 0)
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double[] data = [5, 5, 5, 5, 5];
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double[] expected = [0, 0, 0, 0, 0];
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var accel = new Accel();
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for (int i = 0; i < data.Length; i++)
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{
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var result = accel.Update(new TValue(DateTime.UtcNow, data[i]));
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Assert.Equal(expected[i], result.Value, precision: 9);
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}
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}
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[Fact]
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public void CubicSequence_ProducesLinearAccel()
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{
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// Cubic sequence: 0, 1, 8, 27, 64, 125 (x^3)
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// First diff: 1, 7, 19, 37, 61
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// Second diff (accel): 6, 12, 18, 24 (linear, step of 6)
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double[] data = [0, 1, 8, 27, 64, 125];
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double[] expected = [0, 0, 6, 12, 18, 24];
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var accel = new Accel();
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for (int i = 0; i < data.Length; i++)
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{
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var result = accel.Update(new TValue(DateTime.UtcNow, data[i]));
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Assert.Equal(expected[i], result.Value, precision: 9);
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}
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}
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[Fact]
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public void NegativeQuadratic_ProducesNegativeAccel()
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{
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// Negative quadratic: -x² → 0, -1, -4, -9, -16
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// Accel = -2 (constant)
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double[] data = [0, -1, -4, -9, -16];
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double[] expected = [0, 0, -2, -2, -2];
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var accel = new Accel();
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for (int i = 0; i < data.Length; i++)
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{
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var result = accel.Update(new TValue(DateTime.UtcNow, data[i]));
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Assert.Equal(expected[i], result.Value, precision: 9);
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}
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}
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[Fact]
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public void AlternatingSequence_ProducesAlternatingAccel()
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{
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// Alternating: 0, 10, 0, 10, 0
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// Slope: 10, -10, 10, -10
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// Accel: -20, 20, -20
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double[] data = [0, 10, 0, 10, 0];
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double[] expected = [0, 0, -20, 20, -20];
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var accel = new Accel();
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for (int i = 0; i < data.Length; i++)
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{
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var result = accel.Update(new TValue(DateTime.UtcNow, data[i]));
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Assert.Equal(expected[i], result.Value, precision: 9);
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}
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}
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[Fact]
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public void BatchCalculation_MatchesSyntheticData()
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{
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double[] data = [0, 1, 4, 9, 16, 25];
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double[] expected = [0, 0, 2, 2, 2, 2];
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double[] output = new double[data.Length];
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Accel.Batch(data, output);
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for (int i = 0; i < data.Length; i++)
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{
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Assert.Equal(expected[i], output[i], precision: 9);
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}
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}
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[Fact]
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public void LargeQuadraticSequence_ProducesConstantAccel()
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{
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// Generate 1000 points: f(n) = n² with coefficient 0.5 → accel = 1
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int count = 1000;
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double[] data = new double[count];
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for (int i = 0; i < count; i++)
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{
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data[i] = 0.5 * i * i;
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}
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var accel = new Accel();
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// Skip warmup period (first 2 bars)
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_ = accel.Update(new TValue(DateTime.UtcNow, data[0]));
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_ = accel.Update(new TValue(DateTime.UtcNow, data[1]));
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for (int i = 2; i < count; i++)
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{
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accel.Update(new TValue(DateTime.UtcNow, data[i]));
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Assert.Equal(1.0, accel.Last.Value, precision: 9);
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}
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}
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}
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