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use crate::evaluator::*; use itertools::Itertools; macro_const! { const DOC: &'static str = r#" 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](https://doi.org/10.1093/mnras/stw157) "#; } #[doc = DOC!()] #[derive(Clone, Default, Debug, Serialize, Deserialize, JsonSchema)] pub struct MaximumSlope {} lazy_info!( MAXIMUM_SLOPE_INFO, size: 1, min_ts_length: 2, t_required: true, m_required: true, w_required: false, sorting_required: true, ); impl MaximumSlope { pub fn new() -> Self { Self {} } pub fn doc() -> &'static str { DOC } } impl<T> FeatureEvaluator<T> for MaximumSlope where T: Float, { fn eval(&self, ts: &mut TimeSeries<T>) -> Result<Vec<T>, EvaluatorError> { self.check_ts_length(ts)?; let result = ts.t.as_slice() .iter() .tuple_windows() .map(|(&t1, &t2)| t2 - t1) .zip( ts.m.as_slice() .iter() .tuple_windows() .map(|(&m1, &m2)| m2 - m1), ) .map(|(dt, dm)| T::abs(dm / dt)) .filter(|&x| x.is_finite()) .max_by(|a, b| a.partial_cmp(b).unwrap()) .expect("All points of the light curve have the same time"); Ok(vec![result]) } fn get_info(&self) -> &EvaluatorInfo { &MAXIMUM_SLOPE_INFO } fn get_names(&self) -> Vec<&str> { vec!["maximum_slope"] } fn get_descriptions(&self) -> Vec<&str> { vec!["maximum slope of time-series"] } } #[cfg(test)] #[allow(clippy::unreadable_literal)] #[allow(clippy::excessive_precision)] mod tests { use super::*; use crate::tests::*; check_feature!(MaximumSlope); feature_test!( maximum_slope_positive, [MaximumSlope::new()], [1.0], [0.0_f32, 2.0, 4.0, 5.0, 7.0, 9.0], [0.0_f32, 1.0, 2.0, 3.0, 4.0, 5.0], ); feature_test!( maximum_slope_negative, [MaximumSlope::new()], [1.0], [0.0_f32, 1.0, 2.0, 3.0, 4.0, 5.0], [0.0_f32, 0.5, 1.0, 0.0, 0.5, 1.0], ); }