use super::MetricElem;
use serde::{Deserialize, Serialize};

pub trait VecMetric: MetricElem + From<Vec<f32>> {}

#[derive(Deserialize, Serialize)]
pub struct CosineSimilarity(pub Vec<f32>);
#[derive(Deserialize, Serialize)]
pub struct EuclidianDistance(pub Vec<f32>);
#[derive(Deserialize, Serialize)]
pub struct ManhattenDistance(pub Vec<f32>);

impl VecMetric for CosineSimilarity {}
impl VecMetric for EuclidianDistance {}
impl VecMetric for ManhattenDistance {}
#[rustfmt::skip] impl From<Vec<f32>> for CosineSimilarity { fn from(value: Vec<f32>) -> Self { Self(value) } }
#[rustfmt::skip] impl From<Vec<f32>> for EuclidianDistance { fn from(value: Vec<f32>) -> Self { Self(value) } }
#[rustfmt::skip] impl From<Vec<f32>> for ManhattenDistance { fn from(value: Vec<f32>) -> Self { Self(value) } }

impl MetricElem for CosineSimilarity {
    fn dist(&self, other: &Self) -> f64 {
        let x = self
            .0
            .iter()
            .zip(other.0.iter())
            .map(|(a, b)| *a * *b)
            .sum::<f32>();
        let mag_a = self.0.iter().map(|x| x.powi(2)).sum::<f32>();
        let mag_b = other.0.iter().map(|x| x.powi(2)).sum::<f32>();
        (x / (mag_a * mag_b).sqrt()) as f64
    }
}
impl MetricElem for EuclidianDistance {
    fn dist(&self, other: &Self) -> f64 {
        self.0
            .iter()
            .zip(other.0.iter())
            .map(|(a, b)| (a - b).powf(2.))
            .sum::<f32>()
            .sqrt() as f64
    }
}
impl MetricElem for ManhattenDistance {
    fn dist(&self, other: &Self) -> f64 {
        self.0
            .iter()
            .zip(other.0.iter())
            .map(|(a, b)| (a - b).abs())
            .sum::<f32>() as f64
    }
}