[−][src]Crate 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 mut ts = TimeSeries::new(&time[..], &magn[..], Some(&magn_err_squared[..])); // Get results and print let result = fe.eval(&mut 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
antifeatures | |
periodogram | |
sorted_vec | |
statistics | |
time_series |
Macros
feat_extr | Constructs a |
lazy_info | Helper for static EvaluatorInfo creation |
transformer_eval | Helper for FeatureEvaluator implementations using time-series transformation. You must implement: |
Structs
Amplitude | Half amplitude of magnitude |
AndersonDarlingNormal | Unbiased Anderson–Darling normality test statistic |
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 $\langle m \rangle$ |
Bins | Bins — sampled time series |
Cusum | Cusum — a range of cumulative sums |
Eta | Von Neummann $\eta$ |
EtaE | $\eta^e$ — modernisation of Eta for unevenly time series |
ExcessVariance | Measure of the variability amplitude |
FeatureExtractor | The engine that extracts features one by one |
InterPercentileRange | Inter-percentile range |
Kurtosis | Excess kurtosis of magnitude |
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 sub-sequential observations |
Mean | Mean magnitude |
MeanVariance | Standard deviation to mean ratio |
Median | Median magnitude |
MedianAbsoluteDeviation | Median of the absolute value of the difference between magnitude and its median |
MedianBufferRangePercentage | Fraction of observations inside $\mathrm{Median}(m) \pm q \times (\max(m) - \min(m))$ interval |
MedianNyquistFreq | $\Delta t$ is the median time interval between observations |
PercentAmplitude | Maximum deviation of magnitude from its median |
PercentDifferenceMagnitudePercentile | Ratio of $p$th inter-percentile range 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 |
Enums
EvaluatorError |
Traits
FeatureEvaluator | The trait each feature should implement |
Float | |
NyquistFreq | Derive Nyquist frequency from time series |
PeriodogramPower | Periodogram execution algorithm |
Functions
fit_straight_line |
Type Definitions
VecFE |