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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
}
}
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