Struct light_curve_feature::Periodogram

pub struct Periodogram<T> { /* fields omitted */ }

A number of features based on Lomb–Scargle periodogram

Periodogram $P(\omega)$ is an estimate of spectral density of unevenly time series. Periodogram::new's peaks argument corresponds to a number of the most significant spectral density peaks to return. For each peak its period and "signal to noise" ratio is returned.

$$ \mathrm{signal~to~noise~of~peak} \equiv \frac{P(\omega_\mathrm{peak}) - \langle P(\omega) \rangle}{\sigma_{P(\omega)}}. $$

Periodogram can accept another dyn FeatureEvaluator for feature extraction from periodogram as it was time series without observation errors. You can even pass one Periodogram to another one if you are crazy enough

• Depends on: time, magnitude
• Minimum number of observations: 2
• Number of features: $2 \times \mathrm{peaks}~+...$

Implementations

impl<T> Periodogram<T> where
    T: Float, 

pub fn new(peaks: usize) -> Self

pub fn set_freq_resolution(&mut self, resolution: f32) -> &mut Self

pub fn set_max_freq_factor(&mut self, max_freq_factor: f32) -> &mut Self

pub fn set_nyquist(&mut self, nyquist: Box<dyn NyquistFreq<T>>) -> &mut Self

pub fn add_features(&mut self, features: VecFE<T>) -> &mut Self

pub fn set_periodogram_algorithm(
    &mut self,
    periodogram_power: fn() -> Box<dyn PeriodogramPower<T>>
) -> &mut Self

pub fn init_thread_local_fft_plan(n: &[usize])

Trait Implementations

impl<T> Default for Periodogram<T> where
    T: Float, 

fn default() -> Self

Returns the "default value" for a type.

impl<T> FeatureEvaluator<T> for Periodogram<T> where
    T: Float, 

fn eval(&self, ts: &mut TimeSeries<T>) -> Vec<T>

Should return the non-empty vector of feature values. The length and feature order should correspond to get_names() output

fn get_names(&self) -> Vec<&str>

Should return the non-empty vector of feature names. The length and feature order should correspond to eval() output

fn size_hint(&self) -> usize

Should return the size of vectors returned by eval() and get_names()