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use crate::evaluator::*;
use crate::fit::fit_straight_line;
#[derive(Clone, Default, Debug)]
pub struct LinearFit {}
impl LinearFit {
pub fn new() -> Self {
Self {}
}
}
lazy_info!(
LINEAR_FIT_INFO,
size: 3,
min_ts_length: 3,
t_required: true,
m_required: true,
w_required: true,
sorting_required: true,
);
impl<T> FeatureEvaluator<T> for LinearFit
where
T: Float,
{
fn eval(&self, ts: &mut TimeSeries<T>) -> Result<Vec<T>, EvaluatorError> {
self.check_ts_length(ts)?;
let result = fit_straight_line(ts, true);
Ok(vec![
result.slope,
T::sqrt(result.slope_sigma2),
result.reduced_chi2,
])
}
fn get_info(&self) -> &EvaluatorInfo {
&LINEAR_FIT_INFO
}
fn get_names(&self) -> Vec<&str> {
vec![
"linear_fit_slope",
"linear_fit_slope_sigma",
"linear_fit_reduced_chi2",
]
}
}
#[cfg(test)]
#[allow(clippy::unreadable_literal)]
#[allow(clippy::excessive_precision)]
mod tests {
use super::*;
use crate::tests::*;
eval_info_test!(linear_fit_info, LinearFit::default());
feature_test!(
linear_fit,
[Box::new(LinearFit::default())],
[1.0544186045473263, 0.7963978113902943, 0.013781209302325587],
[0.0_f32, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0],
[0.0_f32, 0.01, 0.04, 0.09, 0.16, 0.25, 0.36, 0.49, 0.64, 0.81, 1.0],
Some(&[1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0]),
);
}