76 lines
2.6 KiB
Rust
76 lines
2.6 KiB
Rust
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//! Module containing various distance metric functions.
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//!
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//! All of these functions are intended to be used with the
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//! [custom_distance](Song::custom_distance) method, or with
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//! [playlist_from_songs_custom_distance](Library::playlist_from_song_custom_distance).
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//!
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//! They will yield different styles of playlists, so don't hesitate to
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//! experiment with them if the default (euclidean distance for now) doesn't
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//! suit you.
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use crate::NUMBER_FEATURES;
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#[cfg(doc)]
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use crate::{Library, Song};
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use ndarray::{Array, Array1};
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/// Convenience trait for user-defined distance metrics.
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pub trait DistanceMetric: Fn(&Array1<f32>, &Array1<f32>) -> f32 {}
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impl<F> DistanceMetric for F where F: Fn(&Array1<f32>, &Array1<f32>) -> f32 {}
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/// Return the [euclidean
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/// distance](https://en.wikipedia.org/wiki/Euclidean_distance#Higher_dimensions)
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/// between two vectors.
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pub fn euclidean_distance(a: &Array1<f32>, b: &Array1<f32>) -> f32 {
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// Could be any square symmetric positive semi-definite matrix;
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// just no metric learning has been done yet.
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// See https://lelele.io/thesis.pdf chapter 4.
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let m = Array::eye(NUMBER_FEATURES);
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(a - b).dot(&m).dot(&(a - b)).sqrt()
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}
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/// Return the [cosine
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/// distance](https://en.wikipedia.org/wiki/Cosine_similarity#Angular_distance_and_similarity)
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/// between two vectors.
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pub fn cosine_distance(a: &Array1<f32>, b: &Array1<f32>) -> f32 {
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let similarity = a.dot(b) / (a.dot(a).sqrt() * b.dot(b).sqrt());
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1. - similarity
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}
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#[cfg(test)]
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mod test {
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use super::*;
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use ndarray::arr1;
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#[test]
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fn test_euclidean_distance() {
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let a = arr1(&[
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1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 0.,
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]);
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let b = arr1(&[
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0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.,
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]);
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assert_eq!(euclidean_distance(&a, &b), 4.242640687119285);
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let a = arr1(&[0.5; 20]);
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let b = arr1(&[0.5; 20]);
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assert_eq!(euclidean_distance(&a, &b), 0.);
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assert_eq!(euclidean_distance(&a, &b), 0.);
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}
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#[test]
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fn test_cosine_distance() {
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let a = arr1(&[
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1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 0.,
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]);
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let b = arr1(&[
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0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.,
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]);
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assert_eq!(cosine_distance(&a, &b), 0.7705842661294382);
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let a = arr1(&[0.5; 20]);
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let b = arr1(&[0.5; 20]);
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assert_eq!(cosine_distance(&a, &b), 0.);
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assert_eq!(cosine_distance(&a, &b), 0.);
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}
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}
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