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