Struct light_curve_feature::Bins

pub struct Bins<T: Float> { /* fields omitted */ }

Bins — sampled time series

Binning time series to bins with width $\mathrm{window}$ with respect to some $\mathrm{offset}$. $j-th$ bin boundaries are $[j \cdot \mathrm{window} + \mathrm{offset}; (j + 1) \cdot \mathrm{window} + \mathrm{offset}]$. Binned time series is defined by $$ t_j^* = (j + \frac12) \cdot \mathrm{window} + \mathrm{offset}, $$ $$ m_j^* = \frac{\sum{m_i / \delta_i^2}}{\sum{\delta_i^{-2}}}, $$ $$ \delta_j^* = \frac{N_j}{\sum{\delta_i^{-2}}}, $$ where $N_j$ is a number of sampling observations and all sums are over observations inside considering bin

• Depends on: time, magnitude, magnitude error
• Minimum number of observations: 1 (or as required by sub-features)
• Number of features: $...$

Implementations

impl<T> Bins<T> where
    T: Float, 

pub fn new(window: T, offset: T) -> Self

pub fn set_window(&mut self, window: T) -> &mut Self

pub fn set_offset(&mut self, offset: T) -> &mut Self

pub fn add_feature(
    &mut self,
    feature: Box<dyn FeatureEvaluator<T>>
) -> &mut Self

Extend a feature to extract from binned time series

Trait Implementations

impl<T: Clone + Float> Clone for Bins<T>

fn clone(&self) -> Bins<T>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<T: Debug + Float> Debug for Bins<T>

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

Formats the value using the given formatter.

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

fn default() -> Self

Returns the "default value" for a type.

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

fn eval(&self, ts: &mut TimeSeries<'_, T>) -> Result<Vec<T>, EvaluatorError>

Should return the vector of feature values

fn eval_or_fill(&self, ts: &mut TimeSeries<'_, T>, fill_value: T) -> Vec<T>

fn get_info(&self) -> &EvaluatorInfo

Get feature evaluator meta-information

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

Should return the 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()

fn min_ts_length(&self) -> usize

Should return minimum time series length to successfully find feature value

fn is_t_required(&self) -> bool

fn is_m_required(&self) -> bool

fn is_w_required(&self) -> bool

fn is_sorting_required(&self) -> bool

fn check_ts_length(
    &self,
    ts: &TimeSeries<'_, T>
) -> Result<usize, EvaluatorError>