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QuanTAlib/lib/numerics/slope/Slope.Validation.Tests.cs
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2026-02-10 21:33:16 -08:00

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C#

namespace QuanTAlib.Tests;
/// <summary>
/// Validation tests for Slope using synthetic data with known mathematical results.
/// </summary>
public class SlopeValidationTests
{
[Fact]
public void LinearSequence_ProducesConstantSlope()
{
// Linear sequence: 0, 2, 4, 6, 8, 10 (slope = 2)
double[] data = [0, 2, 4, 6, 8, 10];
double[] expected = [0, 2, 2, 2, 2, 2]; // First is 0 (no history), rest are 2
var slope = new Slope();
for (int i = 0; i < data.Length; i++)
{
var result = slope.Update(new TValue(DateTime.UtcNow, data[i]));
Assert.Equal(expected[i], result.Value, precision: 9);
}
}
[Fact]
public void ConstantSequence_ProducesZeroSlope()
{
// Constant sequence: 5, 5, 5, 5, 5 (slope = 0)
double[] data = [5, 5, 5, 5, 5];
double[] expected = [0, 0, 0, 0, 0];
var slope = new Slope();
for (int i = 0; i < data.Length; i++)
{
var result = slope.Update(new TValue(DateTime.UtcNow, data[i]));
Assert.Equal(expected[i], result.Value, precision: 9);
}
}
[Fact]
public void DecreasingSequence_ProducesNegativeSlope()
{
// Decreasing sequence: 10, 7, 4, 1, -2 (slope = -3)
double[] data = [10, 7, 4, 1, -2];
double[] expected = [0, -3, -3, -3, -3];
var slope = new Slope();
for (int i = 0; i < data.Length; i++)
{
var result = slope.Update(new TValue(DateTime.UtcNow, data[i]));
Assert.Equal(expected[i], result.Value, precision: 9);
}
}
[Fact]
public void QuadraticSequence_ProducesLinearSlope()
{
// Quadratic sequence: 0, 1, 4, 9, 16, 25 (x^2)
// Slope: n^2 - (n-1)^2 = 2n - 1 → 1, 3, 5, 7, 9
double[] data = [0, 1, 4, 9, 16, 25];
double[] expected = [0, 1, 3, 5, 7, 9];
var slope = new Slope();
for (int i = 0; i < data.Length; i++)
{
var result = slope.Update(new TValue(DateTime.UtcNow, data[i]));
Assert.Equal(expected[i], result.Value, precision: 9);
}
}
[Fact]
public void AlternatingSequence_ProducesAlternatingSlope()
{
// Alternating: 0, 10, 0, 10, 0
double[] data = [0, 10, 0, 10, 0];
double[] expected = [0, 10, -10, 10, -10];
var slope = new Slope();
for (int i = 0; i < data.Length; i++)
{
var result = slope.Update(new TValue(DateTime.UtcNow, data[i]));
Assert.Equal(expected[i], result.Value, precision: 9);
}
}
[Fact]
public void FibonacciSequence_ProducesCorrectSlope()
{
// Fibonacci: 1, 1, 2, 3, 5, 8, 13
// Slope: 0, 1, 1, 2, 3, 5
double[] data = [1, 1, 2, 3, 5, 8, 13];
double[] expected = [0, 0, 1, 1, 2, 3, 5];
var slope = new Slope();
for (int i = 0; i < data.Length; i++)
{
var result = slope.Update(new TValue(DateTime.UtcNow, data[i]));
Assert.Equal(expected[i], result.Value, precision: 9);
}
}
[Fact]
public void BatchCalculation_MatchesSyntheticData()
{
double[] data = [0, 2, 4, 6, 8, 10];
double[] expected = [0, 2, 2, 2, 2, 2];
double[] output = new double[data.Length];
Slope.Batch(data, output);
for (int i = 0; i < data.Length; i++)
{
Assert.Equal(expected[i], output[i], precision: 9);
}
}
[Fact]
public void LargeLinearSequence_ProducesConstantSlope()
{
// Generate 1000 points with slope = 0.5
int count = 1000;
double[] data = new double[count];
for (int i = 0; i < count; i++)
{
data[i] = 100.0 + i * 0.5;
}
var slope = new Slope();
// First element - no previous value, slope = 0
slope.Update(new TValue(DateTime.UtcNow, data[0]));
Assert.Equal(0.0, slope.Last.Value, precision: 9);
// Rest should have constant slope of 0.5
for (int i = 1; i < count; i++)
{
slope.Update(new TValue(DateTime.UtcNow, data[i]));
Assert.Equal(0.5, slope.Last.Value, precision: 9);
}
}
}