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use crate::evaluator::*;

/// Number of observations
///
/// $$
/// N
/// $$
///
/// - Depends on: nothing
/// - Minimum number of observations: **0**
/// - Number of features: **1**
#[derive(Clone, Default, Debug)]
pub struct ObservationCount {}

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

lazy_info!(
    OBSERVATION_COUNT_INFO,
    size: 1,
    min_ts_length: 0,
    t_required: false,
    m_required: false,
    w_required: false,
    sorting_required: false,
);

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

    fn get_info(&self) -> &EvaluatorInfo {
        &OBSERVATION_COUNT_INFO
    }

    fn get_names(&self) -> Vec<&str> {
        vec!["ANTIFEATURE_observation_count"]
    }

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

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

    eval_info_test!(observation_count_info, ObservationCount::default());

    feature_test!(
        observation_count,
        [Box::new(ObservationCount::new())],
        [5.0],
        [0.0_f32, 1.0, 2.0, 3.0, 4.0],
    );
}