Struct AutocorrelationPeriodogram 

pub struct AutocorrelationPeriodogram { /* private fields */ }

Ehlers’ Autocorrelation Periodogram — measures the dominant cycle period of the market by correlating a roofing-filtered price with lagged copies of itself and reading off the spectral peak.

From John Ehlers’ Cycle Analytics for Traders (2013, ch. 8):

Filt = RoofingFilter(price)                                   (detrend + denoise)
Corr[lag] = Pearson( Filt[0..AvgLength], Filt[lag..lag+AvgLength] )   for lag = 0..max_period
for each candidate period:
  power[period] = (Σ Corr[N]·cos(2πN/period))² + (Σ Corr[N]·sin(2πN/period))²
R[period]    = 0.2·power[period] + 0.8·R[period]_{t−1}        (EMA across time)
normalise by a decaying max, then
DominantCycle = centre-of-gravity of periods whose normalised power ≥ 0.5

The autocorrelation function emphasises whatever cycle is actually present and suppresses noise; transforming it into a periodogram and taking the power-weighted centre of gravity gives a smooth, robust estimate of the dominant cycle length. That cycle is the key input for every adaptive indicator (adaptive RSI/CCI/stochastic) — set their lookback from it. The output is a period in bars within [min_period, max_period].

The first value lands after max_period + AvgLength inputs. Each update is O(max_period²).

Example

use wickra_core::{Indicator, AutocorrelationPeriodogram};
use std::f64::consts::TAU;

let mut indicator = AutocorrelationPeriodogram::new(10, 48).unwrap();
let mut last = None;
for i in 0..200 {
    last = indicator.update(100.0 + (TAU * f64::from(i) / 20.0).sin() * 5.0);
}
assert!(last.is_some());

Implementations

impl AutocorrelationPeriodogram

pub fn new(min_period: usize, max_period: usize) -> Result<Self>

Construct an autocorrelation periodogram searching cycles in [min_period, max_period].

Errors

Returns Error::PeriodZero if either period is 0, or Error::InvalidPeriod if min_period < AvgLength + 1 or max_period <= min_period.

pub const fn periods(&self) -> (usize, usize)

Configured (min_period, max_period).

pub const fn value(&self) -> Option<f64>

Current dominant-cycle estimate if available.

Trait Implementations

impl Clone for AutocorrelationPeriodogram

fn clone(&self) -> AutocorrelationPeriodogram

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for AutocorrelationPeriodogram

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Indicator for AutocorrelationPeriodogram

type Input = f64

Type of one input data point (typically f64 for a price, or Candle / Tick).

type Output = f64

Type of one output value.

fn update(&mut self, price: f64) -> Option<f64>

Feed one new data point into the indicator and return the freshly computed output, or None if the indicator is still warming up.

fn reset(&mut self)

Reset all internal state, leaving the indicator equivalent to a freshly constructed instance with the same parameters.

fn warmup_period(&self) -> usize

Number of inputs required before the first non-None output can be produced.

fn is_ready(&self) -> bool

Whether the indicator has emitted at least one value since the last reset.

fn name(&self) -> &'static str

Stable, human-readable indicator name. Used by chaining and diagnostics.