namespace QuanTAlib.Tests; /// /// Validation tests for Slope using synthetic data with known mathematical results. /// 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.Calculate(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); } } }