v6

node_modules/yargs/lib/levenshtein.js

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+/*
+Copyright (c) 2011 Andrei Mackenzie
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the "Software"), to deal in
+the Software without restriction, including without limitation the rights to
+use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
+the Software, and to permit persons to whom the Software is furnished to do so,
+subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
+FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
+COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
+IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
+CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+*/
+
+// levenshtein distance algorithm, pulled from Andrei Mackenzie's MIT licensed.
+// gist, which can be found here: https://gist.github.com/andrei-m/982927
+'use strict'
+// Compute the edit distance between the two given strings
+module.exports = function levenshtein (a, b) {
+  if (a.length === 0) return b.length
+  if (b.length === 0) return a.length
+
+  const matrix = []
+
+  // increment along the first column of each row
+  let i
+  for (i = 0; i <= b.length; i++) {
+    matrix[i] = [i]
+  }
+
+  // increment each column in the first row
+  let j
+  for (j = 0; j <= a.length; j++) {
+    matrix[0][j] = j
+  }
+
+  // Fill in the rest of the matrix
+  for (i = 1; i <= b.length; i++) {
+    for (j = 1; j <= a.length; j++) {
+      if (b.charAt(i - 1) === a.charAt(j - 1)) {
+        matrix[i][j] = matrix[i - 1][j - 1]
+      } else {
+        matrix[i][j] = Math.min(matrix[i - 1][j - 1] + 1, // substitution
+          Math.min(matrix[i][j - 1] + 1, // insertion
+            matrix[i - 1][j] + 1)) // deletion
+      }
+    }
+  }
+
+  return matrix[b.length][a.length]
+}