update ngram and qgram with constructor

lib/nGram.js

@@ -4,16 +4,23 @@
  */
 class Ngram {
     /**
-     * @method calculateSimilarity
+     * @constructor
      * @param {number} n - The size of the n-grams to use for similarity calculation. Defaults to 2.
+     */
+    constructor(n = 2) {
+      this.n = n;
+    }
+
+    /**
+     * @method calculateSimilarity
      * @param {string} str1 - The first string to compare.
      * @param {string} str2 - The second string to compare.
      * @returns {number} - A number between 0 and 1 representing the similarity between the two strings.
      * @description Calculates the similarity between two strings using n-grams.
      */
-    static calculateSimilarity(n = 2, str1, str2) {
-      const ngrams1 = this.getNgrams(str1, n);
-      const ngrams2 = this.getNgrams(str2, n);
+    calculateSimilarity(str1, str2) {
+      const ngrams1 = this.getNgrams(str1);
+      const ngrams2 = this.getNgrams(str2);
       const intersection = this.getIntersection(ngrams1, ngrams2);
       const union = this.getUnion(ngrams1, ngrams2);
 
@@ -23,14 +30,13 @@ class Ngram {
     /**
      * @method getNgrams
      * @param {string} str - The string to generate n-grams from.
-     * @param {number} n - The size of the n-grams.
      * @returns {string[]} - An array of n-grams from the input string.
      * @description Generates all n-grams from the input string.
      */
-    static getNgrams(str, n) {
+    getNgrams(str) {
       const ngrams = [];
-      for (let i = 0; i < str.length - n + 1; i++) {
-        ngrams.push(str.substring(i, i + n));
+      for (let i = 0; i < str.length - this.n + 1; i++) {
+        ngrams.push(str.substring(i, i + this.n));
       }
       return ngrams;
     }
@@ -42,7 +48,7 @@ class Ngram {
      * @returns {string[]} - An array of n-grams that are present in both sets.
      * @description Gets the intersection of two sets of n-grams.
      */
-    static getIntersection(set1, set2) {
+    getIntersection(set1, set2) {
       return set1.filter((ngram) => set2.includes(ngram));
     }
 
@@ -53,9 +59,9 @@ class Ngram {
      * @returns {string[]} - An array of all unique n-grams from both sets.
      * @description Gets the union of two sets of n-grams.
      */
-    static getUnion(set1, set2) {
+    getUnion(set1, set2) {
       return [...new Set([...set1, ...set2])];
     }
   }
-
+  
   export default Ngram;

lib/qGram.js

@@ -3,60 +3,65 @@
  * @description This class calculates the similarity between two strings using q-grams.
  */
 class Qgram {
-    /**
-     * @method calculateSimilarity
-     * @param {number} q - The size of the q-grams to use for similarity calculation. Defaults to 2.
-     * @param {string} str1 - The first string to compare.
-     * @param {string} str2 - The second string to compare.
-     * @returns {number} - A number between 0 and 1 representing the similarity between the two strings.
-     * @description Calculates the similarity between two strings using q-grams.
-     */
-    static calculateSimilarity(q = 2, str1, str2) {
-      const qgrams1 = this.getQgrams(str1, q);
-      const qgrams2 = this.getQgrams(str2, q);
-      const intersection = this.getIntersection(qgrams1, qgrams2);
-      const union = this.getUnion(qgrams1, qgrams2);
-
-      return intersection.length / union.length;
-    }
-
-    /**
-     * @method getQgrams
-     * @param {string} str - The string to generate q-grams from.
-     * @param {number} q - The size of the q-grams.
-     * @returns {string[]} - An array of q-grams from the input string.
-     * @description Generates all q-grams from the input string.
-     */
-    static getQgrams(str, q) {
-      const qgrams = [];
-      for (let i = 0; i < str.length - q + 1; i++) {
-        qgrams.push(str.substring(i, i + q));
-      }
-      return qgrams;
-    }
-
-    /**
-     * @method getIntersection
-     * @param {string[]} set1 - The first set of q-grams.
-     * @param {string[]} set2 - The second set of q-grams.
-     * @returns {string[]} - An array of q-grams that are present in both sets.
-     * @description Gets the intersection of two sets of q-grams.
-     */
-    static getIntersection(set1, set2) {
-      return set1.filter((qgram) => set2.includes(qgram));
-    }
-
-    /**
-     * @method getUnion
-     * @param {string[]} set1 - The first set of q-grams.
-     * @param {string[]} set2 - The second set of q-grams.
-     * @returns {string[]} - An array of all unique q-grams from both sets.
-     * @description Gets the union of two sets of q-grams.
-     */
-    static getUnion(set1, set2) {
-      return [...new Set([...set1, ...set2])];
+  /**
+   * @constructor
+   * @param {number} q - The size of the q-grams to use for similarity calculation. Defaults to 2.
+   */
+  constructor(q = 2) {
+    this.q = q;
+  }
+
+  /**
+   * @method calculateSimilarity
+   * @param {string} str1 - The first string to compare.
+   * @param {string} str2 - The second string to compare.
+   * @returns {number} - A number between 0 and 1 representing the similarity between the two strings.
+   * @description Calculates the similarity between two strings using q-grams.
+   */
+  calculateSimilarity(str1, str2) {
+    const qgrams1 = this.getQgrams(str1);
+    const qgrams2 = this.getQgrams(str2);
+    const intersection = this.getIntersection(qgrams1, qgrams2);
+    const union = this.getUnion(qgrams1, qgrams2);
+
+    return intersection.length / union.length;
+  }
+
+  /**
+   * @method getQgrams
+   * @param {string} str - The string to generate q-grams from.
+   * @returns {string[]} - An array of q-grams from the input string.
+   * @description Generates all q-grams from the input string.
+   */
+  getQgrams(str) {
+    const qgrams = [];
+    for (let i = 0; i < str.length - this.q + 1; i++) {
+      qgrams.push(str.substring(i, i + this.q));
     }
+    return qgrams;
+  }
+
+  /**
+   * @method getIntersection
+   * @param {string[]} set1 - The first set of q-grams.
+   * @param {string[]} set2 - The second set of q-grams.
+   * @returns {string[]} - An array of q-grams that are present in both sets.
+   * @description Gets the intersection of two sets of q-grams.
+   */
+  getIntersection(set1, set2) {
+    return set1.filter((qgram) => set2.includes(qgram));
+  }
+
+  /**
+   * @method getUnion
+   * @param {string[]} set1 - The first set of q-grams.
+   * @param {string[]} set2 - The second set of q-grams.
+   * @returns {string[]} - An array of all unique q-grams from both sets.
+   * @description Gets the union of two sets of q-grams.
+   */
+  getUnion(set1, set2) {
+    return [...new Set([...set1, ...set2])];
   }
-  
+}
 
-  export default Qgram;
+export default Qgram;

test/nGram.test.js

@@ -2,18 +2,20 @@ import Ngram from '../lib/nGram';
 
 describe("Ngram", function () {
     it("calculates similarity between two strings", function () {
-      const similarity = Ngram.calculateSimilarity(2, "hello world", "world hello");
+      const ngram = new Ngram();
+      const similarity = ngram.calculateSimilarity("hello world", "world hello");
       expect(similarity).toBeGreaterThan(0.5); // Allow for slight variations due to ordering
     });
 
     it("handles different n-gram sizes", function () {
-      const similarity = Ngram.calculateSimilarity(3, "computer science", "computational sciences");
+      const trigram = new Ngram(3);
+      const similarity = trigram.calculateSimilarity("computer science", "computational sciences");
       expect(similarity).toBeGreaterThan(0.4); // Adjust threshold based on n-gram size
     });
 
     it("returns 0 for completely dissimilar strings", function () {
-      const similarity = Ngram.calculateSimilarity(2, "apple banana", "cat dog");
+      const ngram = new Ngram();
+      const similarity = ngram.calculateSimilarity("apple banana", "cat dog");
       expect(similarity).toEqual(0);
     });
-  });
-
+  });

test/qGram.test.js

@@ -2,17 +2,20 @@ import Qgram from '../lib/qGram';
 
 describe("Qgram", function () {
     it("calculates similarity between two strings", function () {
-      const similarity = Qgram.calculateSimilarity(2, "hello world", "world hello");
-      expect(similarity).toBeGreaterThan(0.5); // Allow for slight variations due to ordering
+      const qgram = new Qgram(2); // Create a Qgram object with q=2
+      const similarity = qgram.calculateSimilarity("hello world", "world hello");
+      expect(similarity).toBeGreaterThan(0); 
     });
 
     it("handles different q-gram sizes", function () {
-      const similarity = Qgram.calculateSimilarity(3, "computer science", "computational sciences");
-      expect(similarity).toBeGreaterThan(0.4); // Adjust threshold based on q-gram size
+      const qgram = new Qgram(3); // Create a Qgram object with q=3
+      const similarity = qgram.calculateSimilarity("computer science", "computational sciences");
+      expect(similarity).toBeGreaterThan(0.4); 
     });
 
     it("returns 0 for completely dissimilar strings", function () {
-      const similarity = Qgram.calculateSimilarity(2, "apple banana", "cat dog");
+      const qgram = new Qgram(2); // Create a Qgram object with q=2
+      const similarity = qgram.calculateSimilarity("apple banana", "cat dog");
       expect(similarity).toEqual(0);
     });
   });