feat!: move ruzicka from distances to similarities

README.md

@@ -127,12 +127,6 @@ $d(p,q)=1-\frac{\sum\limits_{i=1}^{n}{min(p_i,q_i)}}{\sum\limits_{i=1}^{n}{p_i+q
 
 Note: distance between 2 identical vectors is 0.5 !
 
-- `ruzicka(p, q)`
-
-Returns the [Ruzicka similarity](http://www.naun.org/main/NAUN/ijmmas/mmmas-49.pdf) between vectors p and q. The matching distance is `soergel`.
-
-$s(p,q)=\frac{\sum\limits_{i=1}^{n}{min(p_i,q_i)}}{\sum\limits_{i=1}^{n}{max(p_i,q_i)}}$
-
 - `tanimoto(p, q, [bitVector])`
 
 Returns the [Tanimoto distance](http://www.naun.org/main/NAUN/ijmmas/mmmas-49.pdf) between vectors p and q, and accepts the bitVector use, see the test case for an example
@@ -331,6 +325,12 @@ $s(p,q)=\frac{\sum\limits_{i=1}^{n}{p_i\cdot{q_i}}}{\sum\limits_{i=1}^{n}{p_i^2}
 
 Returns the [Pearson correlation](https://en.wikipedia.org/wiki/Pearson_correlation_coefficient) between vectors p and q, i.e. the cosine similarity of the mean-centred vectors
 
+- `ruzicka(p, q)`
+
+Returns the [Ruzicka similarity](http://www.naun.org/main/NAUN/ijmmas/mmmas-49.pdf), also known as the [weighted Jaccard similarity](https://en.wikipedia.org/wiki/Jaccard_index#Weighted_Jaccard_similarity_and_distance), between vectors p and q. The matching distance is `soergel`.
+
+$s(p,q)=\frac{\sum\limits_{i=1}^{n}{min(p_i,q_i)}}{\sum\limits_{i=1}^{n}{max(p_i,q_i)}}$
+
 - `dice(p, q)`
 
 Returns the [Dice similarity](http://www.naun.org/main/NAUN/ijmmas/mmmas-49.pdf) between vectors p and q

scripts/similarity.js

@@ -15,7 +15,7 @@ let v10 = [-0.4, 0.4];
 let v11 = [-0.6, 0.7];
 
 for (let algorithm in distance) {
-  if (algorithm.match(/fidelity|harmonicMean|innerProduct|ruzicka/)) continue;
+  if (algorithm.match(/fidelity|harmonicMean|innerProduct/)) continue;
   if (algorithm.match(/minkowski/) && algorithm.match(/motyka/)) continue; // does not give a 0 with identical vector
   let result = { algorithm };
   let callback = distance[algorithm];

src/distances.ts

@@ -62,8 +62,6 @@ export * from './distances/pearson.ts';
 
 export * from './distances/probabilisticSymmetric.ts';
 
-export * from './distances/ruzicka.ts';
-
 export * from './distances/soergel.ts';
 
 export * from './distances/sorensen.ts';

src/similarities.ts

@@ -12,6 +12,8 @@ export * from './similarities/motyka.ts';
 
 export * from './similarities/pearson.ts';
 
+export * from './similarities/ruzicka.ts';
+
 export * from './similarities/squaredChord.ts';
 
 export * from './similarities/tanimoto.ts';

src/distances/__tests__/ruzicka.test.ts → src/similarities/__tests__/ruzicka.test.ts

@@ -1,38 +1,42 @@
 import { expect, test } from 'vitest';
 
-import { distance } from '../../index.ts';
+import { distance, similarity } from '../../index.ts';
 
 const v1 = [0.2, 0.4, 0.3, 0.1];
 const v2 = [0.3, 0.2, 0.3, 0.2];
 
 test('should be correct', () => {
-  expect(distance.ruzicka(v1, v2)).toBe(2 / 3);
+  expect(similarity.ruzicka(v1, v2)).toBe(2 / 3);
 });
 
 test('should be 1 for identical vectors, not 0 as a distance would be', () => {
-  expect(distance.ruzicka(v1, v1)).toBe(1);
+  expect(similarity.ruzicka(v1, v1)).toBe(1);
   expect(distance.soergel(v1, v1)).toBe(0);
 });
 
 test('should grow as the vectors get more similar', () => {
-  const far = distance.ruzicka([1, 0], [0, 1]);
-  const near = distance.ruzicka([1, 0], [0.9, 0.1]);
+  const far = similarity.ruzicka([1, 0], [0, 1]);
+  const near = similarity.ruzicka([1, 0], [0.9, 0.1]);
 
   expect(far).toBe(0);
   expect(near).toBeCloseTo(0.818181, 5);
   expect(near).toBeGreaterThan(far);
 });
 
 test('should be the complement of the soergel distance', () => {
-  expect(1 - distance.ruzicka(v1, v2)).toBeCloseTo(
+  expect(1 - similarity.ruzicka(v1, v2)).toBeCloseTo(
     distance.soergel(v1, v2),
     10,
   );
 });
 
 test('should be the complement of the tanimoto distance', () => {
-  expect(1 - distance.ruzicka(v1, v2)).toBeCloseTo(
+  expect(1 - similarity.ruzicka(v1, v2)).toBeCloseTo(
     distance.tanimoto(v1, v2),
     10,
   );
 });
+
+test('should not be exported as a distance', () => {
+  expect(distance).not.toHaveProperty('ruzicka');
+});

src/distances/ruzicka.ts → src/similarities/ruzicka.ts

@@ -1,7 +1,10 @@
 import type { NumberArray } from 'cheminfo-types';
 /**
- *Returns the Ruzicka similarity between vectors a and b
+ *Returns the Ruzicka similarity between vectors a and b, also known as the
+ * weighted Jaccard similarity. It is 1 for identical vectors; the matching
+ * distance is `soergel`.
  * @link [Ruzicka algorithm](https://www.naun.org/main/NAUN/ijmmas/mmmas-49.pdf)
+ * @link [Weighted Jaccard similarity](https://en.wikipedia.org/wiki/Jaccard_index#Weighted_Jaccard_similarity_and_distance)
  * @param a - first vector
  * @param b - second vector
  */