cmpstr - npm Package Compare versions

Comparing version 1.0.0 to 1.0.1

index.js

@@ -6,3 +6,3 @@ /**
  * @author komed3 (Paul Köhler)
- * @version 1.0.0
+ * @version 1.0.1
  * @license MIT
@@ -34,3 +34,3 @@ */
  */
-const bbigrams = ( str ) => {
+const str2bigrams = ( str ) => {
 
@@ -52,6 +52,30 @@ let bigrams = new Set();
 /**
+ * 
+ * @param {String} algo algorithm to use
+ * @param {String} a string 1
+ * @param {String} b string 2
+ * @returns similarity
+ */
+const cpmByAlgo = ( algo, a, b ) => {
+
+    switch( algo ) {
+
+        case 'levenshtein':
+            return levenshtein( a, b );
+
+        case 'diceCoefficient':
+            return diceCoefficient( a, b );
+
+        default:
+            return 0;
+
+    }
+
+};
+
+/**
  * search for closest string
  * @param {String} algo algorithm to use
  * @param {String} test test string
- * @param  {Array} arr targets to test
+ * @param {Array} arr targets to test
  * @returns closest target
@@ -69,18 +93,4 @@ */
 
-        switch( algo ) {
+        pct = cpmByAlgo( algo, test, str );
 
-            case 'levenshtein':
-                pct = levenshtein( test, str );
-                break;
-
-            case 'diceCoefficient':
-                pct = diceCoefficient( test, str );
-                break;
-
-            default:
-                pct = 0;
-                break;
-
-        }
-
         if( pct > best ) {
@@ -104,2 +114,39 @@
 /**
+ * sort best matches to test string
+ * @param {String} algo algorithm to use
+ * @param {String} test test string
+ * @param {Array} arr targets to test
+ * @returns sorted matches
+ */
+const bestMatch = ( algo, test, arr ) => {
+
+    let matches = [],
+        pct;
+
+    /* calculate similarity for each arr items */
+
+    arr.forEach( ( str ) => {
+
+        pct = cpmByAlgo( algo, test, str );
+
+        matches.push( {
+            target: str,
+            match: pct
+        } );
+
+    } );
+
+    /* sort by highest similarity */
+
+    let sorted = matches.sort( ( a, b ) => {
+        return b.match - a.match;
+    } );
+
+    /* return sorted matches */
+
+    return sorted;
+
+};
+
+/**
  * similarity calculations
@@ -241,3 +288,3 @@ * @public
  * @param {String} test test string
- * @param  {Array} arr targets to test
+ * @param {Array} arr targets to test
  * @returns closest target
@@ -252,2 +299,14 @@ */
 /**
+ * sort best matches to test string
+ * @param {String} test test string
+ * @param {Array} arr targets to test
+ * @returns sorted matches
+ */
+const levenshteinMatch = ( test, arr ) => {
+
+    return bestMatch( 'levenshtein', test, arr );
+
+};
+
+/**
  * calculate dice coefficient
@@ -281,4 +340,4 @@ * @param {String} a string 1
 
-        let setA = bbigrams( a ),
-            setB = bbigrams( b );
+        let setA = str2bigrams( a ),
+            setB = str2bigrams( b );
 
@@ -303,3 +362,3 @@ /* calculate dice coefficient */
  * @param {String} test test string
- * @param  {Array} arr targets to test
+ * @param {Array} arr targets to test
  * @returns closest target
@@ -314,2 +373,14 @@ */
 /**
+ * sort best matches to test string
+ * @param {String} test test string
+ * @param {Array} arr targets to test
+ * @returns sorted matches
+ */
+const diceMatch = ( test, arr ) => {
+
+    return bestMatch( 'diceCoefficient', test, arr );
+
+};
+
+/**
  * export module functions
@@ -321,4 +392,6 @@ */
     levenshteinClosest,
+    levenshteinMatch,
     diceCoefficient,
-    diceClosest
+    diceClosest,
+    diceMatch
 };

package.json

@@ -10,3 +10,3 @@ {
   "homepage": "https://github.com/komed3/cmpstr#readme",
-  "version": "1.0.0",
+  "version": "1.0.1",
   "license": "MIT",
@@ -13,0 +13,0 @@ "keywords": [

README.md

@@ -27,12 +27,34 @@ # cmpstr
 
+/**
+ * levenshteinDistance
+ * expected: 3
+ */
 let distance = cmpstr.levenshteinDistance( str1, str2 );
-// expected 3
 
+/**
+ * diceCoefficient
+ * expected: 0.3636363636363636
+ */
 let dice = cmpstr.diceCoefficient( str1, str2 );
-// expected 0.3636363636363636
 
+/**
+ * diceClosest
+ * expected: bestest
+ */
 let closest = cmpstr.diceClosest( 'best', [
   'better', 'bestest', 'well', 'good'
 ] );
-// expected bestest
+
+/**
+ * levenshteinMatch
+ * expected: [
+ *   { target: 'bestest', match: 0.5714285714285714 },
+ *   { target: 'better', match: 0.5 },
+ *   { target: 'well', match: 0.25 },
+ *   { target: 'good', match: 0 }
+ * ]
+ */
+let matches = cmpstr.levenshteinMatch( 'best', [
+  'better', 'bestest', 'well', 'good'
+] );
 ```
@@ -63,2 +85,6 @@
 
+#### ``levenshteinMatch( str, arr )``
+
+Calculates the similarity of all strings contained in the array ``arr`` according to Levenshtein compared to ``str`` and returns an array of all samples sorted by matching in descending order.
+
 ### Sørensen-Dice coefficient
@@ -73,1 +99,5 @@
 As another way to find the best match between the string ``str`` and a given array ``arr`` of samples, this function uses the Sørensen-Dice coefficient. It returns the most matching string as well.
+
+#### ``diceMatch( str, arr )``
+
+Calculates the similarity of all strings contained in the array ``arr`` according to Sørensen-Dice coefficient compared to ``str`` and returns an array of all samples sorted by matching in descending order.

No alert changes

Improved metrics

Total package byte prevSize

11984

23.56%

Lines of code

258

25.24%

Number of lines in readme file

100

40.85%

No dependency changes