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use crate::evaluator::FeatureEvaluator; use crate::float_trait::Float; use crate::time_series::TimeSeries; #[derive(Clone, Default)] pub struct ObservationCount {} impl ObservationCount { pub fn new() -> Self { Self {} } } impl<T> FeatureEvaluator<T> for ObservationCount where T: Float, { fn eval(&self, ts: &mut TimeSeries<T>) -> Vec<T> { vec![ts.lenf()] } fn get_names(&self) -> Vec<&str> { vec!["ANTIFEATURE_observation_count"] } fn size_hint(&self) -> usize { 1 } } #[derive(Clone, Default)] pub struct TimeMean {} impl TimeMean { pub fn new() -> Self { Self {} } } impl<T> FeatureEvaluator<T> for TimeMean where T: Float, { fn eval(&self, ts: &mut TimeSeries<T>) -> Vec<T> { vec![ts.t.get_mean()] } fn get_names(&self) -> Vec<&str> { vec!["ANTIFEATURE_time_mean"] } fn size_hint(&self) -> usize { 1 } } #[derive(Clone, Default)] pub struct TimeStandardDeviation {} impl TimeStandardDeviation { pub fn new() -> Self { Self {} } } impl<T> FeatureEvaluator<T> for TimeStandardDeviation where T: Float, { fn eval(&self, ts: &mut TimeSeries<T>) -> Vec<T> { vec![ts.t.get_std()] } fn get_names(&self) -> Vec<&str> { vec!["ANTIFEATURE_time_standard_deviation"] } fn size_hint(&self) -> usize { 1 } } #[cfg(test)] #[allow(clippy::unreadable_literal)] #[allow(clippy::excessive_precision)] mod tests { use super::*; use crate::extractor::FeatureExtractor; use light_curve_common::all_close; feature_test!( observation_count, [Box::new(ObservationCount::new())], [5.0], [0.0_f32, 1.0, 2.0, 3.0, 4.0], ); feature_test!( time_mean, [Box::new(TimeMean::new())], [14.0], [1.0_f32, 1.0, 1.0, 1.0, 5.0, 6.0, 6.0, 6.0, 99.0], ); feature_test!( time_standard_deviation, [Box::new(TimeStandardDeviation::new())], [1.5811388300841898], [0.0_f32, 1.0, 2.0, 3.0, 4.0], ); }