Struct light_curve_feature::MaximumSlope

pub struct MaximumSlope {}

Maximum slope between two sub-sequential observations

$$ \mathrm{maximum~slope} \equiv \max_{i=0..N-2}\left|\frac{m_{i+1} - m_i}{t_{i+1} - t_i}\right| $$

• Depends on: time, magnitude
• Minimum number of observations: 2
• Number of features: 1

D’Isanto et al. 2016 DOI:10.1093/mnras/stw157

Implementations

impl MaximumSlope

pub fn new() -> Self

Trait Implementations

impl Clone for MaximumSlope

fn clone(&self) -> MaximumSlope

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for MaximumSlope

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

Formats the value using the given formatter.

impl Default for MaximumSlope

fn default() -> MaximumSlope

Returns the "default value" for a type.

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

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

Should return the vector of feature values

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

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>