quantwave_core/indicators/
bandpass.rs

1use crate::indicators::metadata::{IndicatorMetadata, ParamDef};
2use crate::traits::Next;
3use std::f64::consts::PI;
4
5/// BandPass Filter
6///
7/// Based on John Ehlers' "Empirical Mode Decomposition" and "Fourier Series Model".
8/// Isolates cyclic components within a specific frequency band.
9#[derive(Debug, Clone)]
10pub struct BandPass {
11    alpha: f64,
12    beta: f64,
13    price_prev1: f64,
14    price_prev2: f64,
15    bp_history: [f64; 2],
16    count: usize,
17}
18
19impl BandPass {
20    pub fn new(period: usize, bandwidth: f64) -> Self {
21        let beta = (2.0 * PI / period as f64).cos();
22        let gamma = 1.0 / (2.0 * PI * bandwidth / period as f64).cos();
23        let alpha = gamma - (gamma * gamma - 1.0).sqrt();
24
25        Self {
26            alpha,
27            beta,
28            price_prev1: 0.0,
29            price_prev2: 0.0,
30            bp_history: [0.0; 2],
31            count: 0,
32        }
33    }
34}
35
36impl Next<f64> for BandPass {
37    type Output = f64;
38
39    fn next(&mut self, input: f64) -> Self::Output {
40        self.count += 1;
41
42        // BP = .5*(1 - alpha)*(Price - Price[2]) + beta*(1 + alpha)*BP[1] - alpha*BP[2];
43        let bp = 0.5 * (1.0 - self.alpha) * (input - self.price_prev2)
44            + self.beta * (1.0 + self.alpha) * self.bp_history[0]
45            - self.alpha * self.bp_history[1];
46
47        self.bp_history[1] = self.bp_history[0];
48        self.bp_history[0] = bp;
49        self.price_prev2 = self.price_prev1;
50        self.price_prev1 = input;
51
52        bp
53    }
54}
55
56pub const BANDPASS_METADATA: IndicatorMetadata = IndicatorMetadata {
57    name: "BandPass",
58    description: "A bandpass filter that isolates cycle components around a center period.",
59    params: &[
60        ParamDef {
61            name: "period",
62            default: "20",
63            description: "Center period of the passband",
64        },
65        ParamDef {
66            name: "bandwidth",
67            default: "0.1",
68            description: "Relative bandwidth (delta)",
69        },
70    ],
71    formula_source: "https://github.com/lavs9/quantwave/blob/main/references/Ehlers%20Papers/EmpiricalModeDecomposition.pdf",
72    formula_latex: r#"
73\[
74\beta = \cos(360/P), \gamma = 1/\cos(720\delta/P), \alpha = \gamma - \sqrt{\gamma^2 - 1}
75\]
76\[
77BP = 0.5(1 - \alpha)(Price - Price_{t-2}) + \beta(1 + \alpha)BP_{t-1} - \alpha BP_{t-2}
78\]
79"#,
80    gold_standard_file: "bandpass.json",
81    category: "Ehlers DSP",
82};
83
84#[cfg(test)]
85mod tests {
86    use super::*;
87    use crate::traits::Next;
88    use proptest::prelude::*;
89
90    #[test]
91    fn test_bandpass_basic() {
92        let mut bp = BandPass::new(20, 0.1);
93        for i in 0..50 {
94            let val = bp.next(100.0 + (i as f64 * 0.1).sin());
95            assert!(!val.is_nan());
96        }
97    }
98
99    proptest! {
100        #[test]
101        fn test_bandpass_parity(
102            inputs in prop::collection::vec(1.0..100.0, 50..100),
103        ) {
104            let period = 20;
105            let bandwidth = 0.1;
106            let mut bp_obj = BandPass::new(period, bandwidth);
107            let streaming_results: Vec<f64> = inputs.iter().map(|&x| bp_obj.next(x)).collect();
108
109            // Batch implementation
110            let mut batch_results = Vec::with_capacity(inputs.len());
111            let beta = (2.0 * PI / period as f64).cos();
112            let _gamma = 1.0 / (2.0 * PI * 2.0 * bandwidth / period as f64).cos(); // Ehlers uses 720*delta
113            // Wait, Ehlers uses 360/P for Cosine (degrees) which is 2*PI/P for cos (radians).
114            // Ehlers uses 720*delta/P for Cosine which is 4*PI*delta/P for cos.
115            // My alpha/beta in code:
116            // beta = cos(2*PI/P)
117            // gamma = 1/cos(4*PI*delta/P)
118            
119            let alpha = {
120                let g = 1.0 / (2.0 * PI * bandwidth / period as f64).cos();
121                g - (g * g - 1.0).sqrt()
122            };
123
124            let mut p_hist = vec![0.0; inputs.len() + 2];
125            let mut b_hist = vec![0.0; inputs.len() + 2];
126
127            for (i, &input) in inputs.iter().enumerate() {
128                let idx = i + 2;
129                p_hist[idx] = input;
130                let bp = 0.5 * (1.0 - alpha) * (p_hist[idx] - p_hist[idx-2])
131                    + beta * (1.0 + alpha) * b_hist[idx-1]
132                    - alpha * b_hist[idx-2];
133                b_hist[idx] = bp;
134                batch_results.push(bp);
135            }
136
137            for (s, b) in streaming_results.iter().zip(batch_results.iter()) {
138                approx::assert_relative_eq!(s, b, epsilon = 1e-10);
139            }
140        }
141    }
142}
quantwave_core/indicators/bandpass.rs

quantwave_core/indicators/
bandpass.rs
