Crate light_curve_feature

Light curve feature

light-curve-feature is a part of light-curve family that implements extraction of numerous light curve features used in astrophysics.

use light_curve_feature::*;

// Let's find amplitude and reduced Chi-squared of the light curve
let fe = feat_extr!(Amplitude::default(), ReducedChi2::default());
// Define light curve
let time = [0.0, 1.0, 2.0, 3.0, 4.0];
let magn = [-1.0, 2.0, 1.0, 3.0, 4.5];
let magn_err_squared = [0.2, 0.1, 0.5, 0.1, 0.2];
let ts = TimeSeries::new(&time[..], &magn[..], Some(&magn_err_squared[..]));
// Get results and print
let result = fe.eval(ts);
let names = fe.get_names();
println!("{:?}", names.iter().zip(result.iter()).collect::<Vec<_>>());

Re-exports

pub use periodogram::recurrent_sin_cos::RecurrentSinCos;

pub use time_series::TimeSeries;

Modules

periodogram
statistics
time_series

Macros

feat_extr

Constructs a FeatureExtractor object from a list of objects that implement FeatureEvaluator

Structs

Amplitude	Half amplitude of magnitude
AverageNyquistFreq	$\Delta t = \mathrm{duration} / (N - 1)$ is the mean time interval between observations
BeyondNStd	Fraction of observations beyond $n\,\sigma_m$ from the mean magnitude $\langle m \rangle$
Cusum	Cusum — a range of cumulative sums
Eta	Von Neummann $\eta$
EtaE	$\eta^e$ — modernisation of Eta for unevenly time series
FeatureExtractor	The engine that extracts features one by one
Kurtosis	Kurtosis of magnitude $G_2$
LinearFit	The slope, its error and reduced $\chi^2$ of the light curve in the linear fit
LinearTrend	The slope and noise of the light curve without observation errors in the linear fit
MagnitudePercentageRatio	Magnitude percentage ratio
MaximumSlope	Maximum slope between two neighbour observations
Mean	Mean magnitude
MedianAbsoluteDeviation	Median of the absolute value of the difference between magnitude and its median
MedianBufferRangePercentage	Fraction of observations inside $\mathrm{Median}(m) \pm q \times \mathrm{Median}(m)$ interval
MedianNyquistFreq	$\Delta t$ is the median time interval between observations
PercentAmplitude	Maximum deviation of magnitude from its median
PercentDifferenceMagnitudePercentile	Ratio of $p$ percentile interval to the median
Periodogram	A number of features based on Lomb–Scargle periodogram
PeriodogramPowerDirect	Direct periodogram executor
PeriodogramPowerFft	"Fast" (FFT-based) periodogram executor
QuantileNyquistFreq	$\Delta t$ is the $q$th quantile of time intervals between subsequent observations
ReducedChi2	Reduced $\chi^2$ of magnitude measurements
Skew	Skewness of magnitude $G_1$
StandardDeviation	Standard deviation of magnitude $\sigma_m$
StetsonK	Stetson $K$ coefficient described light curve shape
WeightedMean	Weighted mean magnitude

Traits

FeatureEvaluator	The trait each feature should implement
NyquistFreq	Derive Nyquist frequency from time series
PeriodogramPower	Periodogram execution algorithm

Type Definitions

VecFE