Roofing Filter

John Ehlers' bandpass formed by feeding a 2-pole high-pass into a SuperSmoother. The high-pass strips out the trend (periods longer than hp_period) and the SuperSmoother removes noise (periods shorter than lp_period). The result is essentially the 10–48 bar cycle band on default parameters — the canonical pre-filter for cycle-aware oscillators.

Quick reference

Item	Value
Family	Ehlers / Cycle (DSP)
Input type	f64
Output type	f64
Output range	unbounded; centred near zero
Default parameters	lp_period, hp_period required (Ehlers' typical (10, 48))
Warmup period	2 (initial-condition phase)
Interpretation	Cycle-band signal; zero crossings = cycle-momentum reversals

Formula

alpha = (cos(.707·360°/hp_period) + sin(.707·360°/hp_period) - 1)
        / cos(.707·360°/hp_period)

HP_t  = (1 - α/2) · (x_t - x_{t-1}) + (1 - α) · HP_{t-1}

Roofing_t = SuperSmoother(lp_period).update(HP_t)

A single-pole high-pass (not the 2-pole used in Decycler) followed by the SuperSmoother lowpass. The combination passes only the band between lp_period (lower) and hp_period (upper). See crates/wickra-core/src/indicators/roofing_filter.rs.

Parameters

Name	Type	Default	Constraint	Description
lp_period	usize	none	> 1, < hp_period	SuperSmoother critical period (lowpass).
hp_period	usize	none	> 1, > lp_period	High-pass cutoff.

RoofingFilter::new returns Error::PeriodZero for zero periods and Error::InvalidPeriod for lp_period >= hp_period.

Inputs / Outputs

Indicator<Input = f64, Output = f64>. Python: RoofingFilter(lp, hp).batch(prices) returns a 1-D np.ndarray. Node: same shape; update(value) returns number.

Warmup

warmup_period() == 2. The first 2 bars are pass-through initial condition; from bar 3 the recursion runs. Stable output by ~2 · max(lp, hp) / 2 bars.

Edge cases

• Constant input. Both filter outputs decay to zero.
• Trend input. High-pass strips it out; output stays near zero.
• Pure cycle in band. Passes through with mild attenuation; output oscillates around zero with the cycle's amplitude.
• Reset. reset() clears the high-pass state and the inner SuperSmoother.

Examples

Rust

use wickra::{BatchExt, Indicator, RoofingFilter};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let prices: Vec<f64> = (0..200)
        .map(|i| {
            let trend = 100.0 + f64::from(i) * 0.3;
            let cycle = (f64::from(i) * 0.4).sin() * 4.0;
            let noise = (f64::from(i) * 2.0).sin() * 0.5;
            trend + cycle + noise
        })
        .collect();
    let mut rf = RoofingFilter::new(10, 48)?;
    println!("row 100 = {:?}", rf.batch(&prices)[100]);
    // Trend removed, noise smoothed, cycle component preserved
    Ok(())
}

Python

import numpy as np
import wickra as ta

t = np.arange(200)
trend = 100 + t * 0.3
cycle = np.sin(t * 0.4) * 4
noise = np.sin(t * 2.0) * 0.5
prices = trend + cycle + noise
rf = ta.RoofingFilter(10, 48)
print('row 100:', rf.batch(prices)[100])

Node

const wickra = require('wickra');
const rf = new wickra.RoofingFilter(10, 48);
const prices = Array.from({ length: 200 },
  (_, i) => 100 + i * 0.3 + Math.sin(i * 0.4) * 4);
console.log('row 100:', rf.batch(prices)[100]);

Streaming

use wickra::{Indicator, RoofingFilter};

let mut rf = RoofingFilter::new(10, 48).unwrap();
let price_stream: Vec<f64> = Vec::new(); // your live price feed
for px in price_stream {
    let cycle = rf.update(px).unwrap();
    // `cycle` is the band-limited price residual; feed downstream
    // oscillators (e.g. Stochastic) on this instead of raw price
    // for adaptive cycle-aware signals.
}

Interpretation

• Cycle-band signal. The output is the residual price action inside the [lp_period, hp_period] cycle band. Useful as the input to cycle-aware oscillators rather than as a signal in its own right.
• Used by EhlersStochastic. Stochastic computed on Roofing- Filter output rather than raw price is one of the canonical Ehlers cycle indicators — see EhlersStochastic.
• Zero crossings. Mark cycle-momentum reversals. Often used as a confirmation filter rather than as primary entry signal.

Common pitfalls

• Trading the raw Roofing output. It's a pre-filter, not a signal. Stack it under an oscillator (Stoch, RSI, CCI) for trade signals.
• Period ratio. (lp, hp) = (10, 12) gives a near-zero passband — output is noise. Use Ehlers' default (10, 48) or a similar wide ratio.
• High-pass + SuperSmoother stacking order. Reversing the order (SuperSmoother first, then HP) changes the response. Don't roll your own variant if you want canonical Ehlers behaviour.

References

• John F. Ehlers, Cycle Analytics for Traders, Wiley (2013), ch. 7 — Roofing Filter as standard cycle pre-filter.

See also

• SuperSmoother — the lowpass half.
• Decycler — alternative trend extractor.
• EhlersStochastic — direct consumer of the Roofing Filter output.
• Indicators-Overview — full taxonomy.