use crate::evaluator::*;
use crate::sorted_array::SortedArray;
macro_const! {
const DOC: &'static str = r#"
Median of the absolute value of the difference between magnitude and its median
$$
\mathrm{median~absolute~deviation} \equiv \mathrm{Median}\left(|m_i - \mathrm{Median}(m)|\right).
$$
- Depends on: **magnitude**
- Minimum number of observations: **1**
- 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 MedianAbsoluteDeviation {}
lazy_info!(
MEDIAN_ABSOLUTE_DEVIATION_INFO,
MedianAbsoluteDeviation,
size: 1,
min_ts_length: 1,
t_required: false,
m_required: true,
w_required: false,
sorting_required: false,
);
impl MedianAbsoluteDeviation {
pub fn new() -> Self {
Self {}
}
pub fn doc() -> &'static str {
DOC
}
}
impl FeatureNamesDescriptionsTrait for MedianAbsoluteDeviation {
fn get_names(&self) -> Vec<&str> {
vec!["median_absolute_deviation"]
}
fn get_descriptions(&self) -> Vec<&str> {
vec!["median of absolute magnitude deviation from its median"]
}
}
impl<T> FeatureEvaluator<T> for MedianAbsoluteDeviation
where
T: Float,
{
fn eval(&self, ts: &mut TimeSeries<T>) -> Result<Vec<T>, EvaluatorError> {
self.check_ts_length(ts)?;
let m_median = ts.m.get_median();
let sorted_deviation: SortedArray<_> =
ts.m.sample
.mapv(|m| T::abs(m - m_median))
.into_raw_vec()
.into();
Ok(vec![sorted_deviation.median()])
}
}
#[cfg(test)]
#[allow(clippy::unreadable_literal)]
#[allow(clippy::excessive_precision)]
mod tests {
use super::*;
use crate::tests::*;
check_feature!(MedianAbsoluteDeviation);
feature_test!(
median_absolute_deviation,
[MedianAbsoluteDeviation::new()],
[4.0],
[1.0_f32, 1.0, 1.0, 1.0, 5.0, 6.0, 6.0, 6.0, 100.0],
);
}