Struct light_curve_feature::features::BeyondNStd

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

Fraction of observations beyond $n,\sigma_m$ from the mean magnitude $\langle m \rangle$

$$ \mathrm{beyond}~n,\sigma_m \equiv \frac{\sum_i I_{|m - \langle m \rangle| > n,\sigma_m}(m_i)}{N}, $$ where $I$ is the indicator function, $N$ is the number of observations, $\langle m \rangle$ is the mean magnitude and $\sigma_m = \sqrt{\sum_i (m_i - \langle m \rangle)^2 / (N-1)}$ is the magnitude standard deviation.

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

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

Example

use light_curve_feature::*;
use light_curve_common::all_close;
use std::f64::consts::SQRT_2;

let fe = FeatureExtractor::new(vec![BeyondNStd::default(), BeyondNStd::new(2.0)]);
let time = [0.0; 21];  // Doesn't depend on time
let mut magn = vec![0.0; 17];
magn.extend_from_slice(&[SQRT_2, -SQRT_2, 2.0 * SQRT_2, -2.0 * SQRT_2]);
let mut ts = TimeSeries::new_without_weight(&time[..], &magn[..]);
assert_eq!(0.0, ts.m.get_mean());
assert!((1.0 - ts.m.get_std()).abs() < 1e-15);
assert_eq!(vec![4.0 / 21.0, 2.0 / 21.0], fe.eval(&mut ts).unwrap());

Implementations

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

pub fn new(nstd: T) -> Self

pub fn set_name(&mut self, name: String)

pub fn default_nstd() -> T

impl<T> BeyondNStd<T>

pub fn doc() -> &'static str

Trait Implementations

impl<T: Clone> Clone for BeyondNStd<T>

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

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<T: Debug> Debug for BeyondNStd<T>

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

Formats the value using the given formatter.

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

fn default() -> Self

Returns the “default value” for a type.

impl<'de, T> Deserialize<'de> for BeyondNStd<T> where
    T: Float, 

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl<T: Float> EvaluatorInfoTrait for BeyondNStd<T>

fn get_info(&self) -> &EvaluatorInfo

Get feature evaluator meta-information

fn size_hint(&self) -> usize

Size of vectors returned by eval(), get_names() and get_descriptions()

fn min_ts_length(&self) -> usize

Minimum time series length required to successfully evaluate feature

fn is_t_required(&self) -> bool

If time array used by the feature

fn is_m_required(&self) -> bool

If magnitude array is used by the feature

fn is_w_required(&self) -> bool

If weight array is used by the feature

fn is_sorting_required(&self) -> bool

If feature requires time-sorting on the input TimeSeries

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

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

Vector of feature values or EvaluatorError

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

Returns vector of feature values and fill invalid components with given value

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

Checks if TimeSeries has enough points to evaluate the feature

impl<T> FeatureNamesDescriptionsTrait for BeyondNStd<T> where
    T: Float, 

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

Vector of feature names. The length and feature order corresponds to eval() output

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

Vector of feature descriptions. The length and feature order corresponds to eval() output

impl<T> From<BeyondNStd<T>> for Feature<T> where
    T: Float, 

fn from(v: BeyondNStd<T>) -> Feature<T>

Performs the conversion.

impl<T> JsonSchema for BeyondNStd<T> where
    T: Float, 

fn is_referenceable() -> bool

Whether JSON Schemas generated for this type should be re-used where possible using the $ref keyword.

fn schema_name() -> String

The name of the generated JSON Schema.

fn json_schema(gen: &mut SchemaGenerator) -> Schema

Generates a JSON Schema for this type.

impl<T> Serialize for BeyondNStd<T> where
    T: Float, 

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where
    __S: Serializer, 

Serialize this value into the given Serde serializer.

impl<T> TryInto<BeyondNStd<T>> for Feature<T> where
    T: Float, 

type Error = &'static str

The type returned in the event of a conversion error.

fn try_into(
    self
) -> Result<BeyondNStd<T>, <Self as TryInto<BeyondNStd<T>>>::Error>

Performs the conversion.