Add ordered_pairs method to FastPair
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@@ -179,6 +179,18 @@ impl<'a, T: RealNumber + FloatNumber, M: Array2<T>> FastPair<'a, T, M> {
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}
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}
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///
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/// Return order dissimilarities from closest to furthest
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///
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#[allow(dead_code)]
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pub fn ordered_pairs(&self) -> std::vec::IntoIter<&PairwiseDistance<T>> {
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// improvement: implement this to return `impl Iterator<Item = &PairwiseDistance<T>>`
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// need to implement trait `Iterator` for `Vec<&PairwiseDistance<T>>`
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let mut distances = self.distances.values().collect::<Vec<&PairwiseDistance<T>>>();
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distances.sort_by(|a, b| a.partial_cmp(b).unwrap());
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distances.into_iter()
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}
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//
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// Compute distances from input to all other points in data-structure.
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// input is the row index of the sample matrix
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@@ -590,4 +602,39 @@ mod tests_fastpair {
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assert_eq!(closest, min_dissimilarity);
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}
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#[test]
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fn fastpair_ordered_pairs() {
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let x = DenseMatrix::<f64>::from_2d_array(&[
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&[5.1, 3.5, 1.4, 0.2],
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&[4.9, 3.0, 1.4, 0.2],
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&[4.7, 3.2, 1.3, 0.2],
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&[4.6, 3.1, 1.5, 0.2],
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&[5.0, 3.6, 1.4, 0.2],
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&[5.4, 3.9, 1.7, 0.4],
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&[4.9, 3.1, 1.5, 0.1],
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&[7.0, 3.2, 4.7, 1.4],
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&[6.4, 3.2, 4.5, 1.5],
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&[6.9, 3.1, 4.9, 1.5],
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&[5.5, 2.3, 4.0, 1.3],
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&[6.5, 2.8, 4.6, 1.5],
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&[4.6, 3.4, 1.4, 0.3],
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&[5.0, 3.4, 1.5, 0.2],
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&[4.4, 2.9, 1.4, 0.2],
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]);
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let fastpair = FastPair::new(&x).unwrap();
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let ordered = fastpair.ordered_pairs();
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let mut previous: f64 = -1.0;
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for p in ordered {
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if previous == -1.0 {
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previous = p.distance.unwrap();
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} else {
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let current = p.distance.unwrap();
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assert!(current >= previous);
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previous = current;
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}
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}
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}
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}
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