Struct ExponentialMovingAverage 

pub struct ExponentialMovingAverage { /* private fields */ }

Exponential Moving Average (EMA) filter.

Each new value is blended with the running average: EMA_new = alpha * value + (1 - alpha) * EMA_old

The first pushed value initializes the EMA directly.

Example

use numrs2::new_modules::streaming_stats::ExponentialMovingAverage;

let mut ema = ExponentialMovingAverage::new(0.5).expect("valid smoothing factor");
ema.push(10.0);
assert!((ema.value().expect("EMA has data") - 10.0).abs() < 1e-10);
ema.push(20.0);
assert!((ema.value().expect("EMA has data") - 15.0).abs() < 1e-10);

Implementations

impl ExponentialMovingAverage

pub fn new(alpha: f64) -> Result<Self>

Creates a new EMA with the given smoothing factor alpha.

Errors

Returns an error if alpha is not in the interval (0, 1].

pub fn alpha(&self) -> f64

Returns the smoothing factor alpha.

pub fn push(&mut self, value: f64)

Pushes a new observation. The first value initializes the EMA; subsequent values are exponentially blended.

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

Returns the current EMA value, or None if no values have been pushed.

pub fn reset(&mut self)

Resets the EMA to its initial empty state, preserving the alpha parameter.

Trait Implementations

impl Clone for ExponentialMovingAverage

fn clone(&self) -> ExponentialMovingAverage

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ExponentialMovingAverage

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

Formats the value using the given formatter.