light-curve-feature 0.5.2

Feature extractor from noisy time series
Documentation
use crate::evaluator::*;

macro_const! {
    const DOC: &str = r#"
Median magnitude

$$
\mathrm{Median}(m_i)
$$

- Depends on: **magnitude**
- Minimum number of observations: **1**
- Number of features: **1**
"#;
}

#[doc = DOC!()]
#[derive(Clone, Default, Debug, Serialize, Deserialize, JsonSchema)]
pub struct Median {}

lazy_info!(
    MEDIAN_INFO,
    Median,
    size: 1,
    min_ts_length: 1,
    t_required: false,
    m_required: true,
    w_required: false,
    sorting_required: false,
);

impl Median {
    pub fn new() -> Self {
        Self {}
    }

    pub fn doc() -> &'static str {
        DOC
    }
}

impl FeatureNamesDescriptionsTrait for Median {
    fn get_names(&self) -> Vec<&str> {
        vec!["median"]
    }

    fn get_descriptions(&self) -> Vec<&str> {
        vec!["median magnitude"]
    }
}

impl<T> FeatureEvaluator<T> for Median
where
    T: Float,
{
    fn eval(&self, ts: &mut TimeSeries<T>) -> Result<Vec<T>, EvaluatorError> {
        self.check_ts_length(ts)?;
        Ok(vec![ts.m.get_median()])
    }
}

#[cfg(test)]
#[allow(clippy::unreadable_literal)]
#[allow(clippy::excessive_precision)]
mod tests {
    use super::*;
    use crate::tests::*;

    check_feature!(Median);

    feature_test!(
        median_odd,
        [Median::new()],
        [3.0],
        [-99.0, 0.0, 3.0, 3.1, 3.2],
    );

    feature_test!(
        median_even,
        [Median::new()],
        [1.5],
        [-99.0, 0.0, 4.0, 3.0, 2.0, 1.0],
    );
}