# All files / src/utils fuzzy.js

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     module.exports = function (text, pattern, options) {
      // Aproximately where in the text is the pattern expected to be found?
      var Match_Location = options.location || 0

      //Determines how close the match must be to the fuzzy location (specified above). An exact letter match which is 'distance' characters away from the fuzzy location would score as a complete mismatch. A distance of '0' requires the match be at the exact location specified, a threshold of '1000' would require a perfect match to be within 800 characters of the fuzzy location to be found using a 0.8 threshold.
      var Match_Distance = options.distance || 100

      // At what point does the match algorithm give up. A threshold of '0.0' requires a perfect match (of both letters and location), a threshold of '1.0' would match anything.
      var Match_Threshold = options.threshold || 0.4

      Iif (pattern === text) return true // Exact match
      Iif (pattern.length > 32) return false // This algorithm cannot be used

      // Set starting location at beginning text and initialise the alphabet.
      var loc = Match_Location,
        s = (function () {
          var q = {},
            i

          for (i = 0; i < pattern.length; i++) {
            q[pattern.charAt(i)] = 0
          }

          for (i = 0; i < pattern.length; i++) {
            q[pattern.charAt(i)] |= 1 << (pattern.length - i - 1)
          }

          return q
        })()

      // Compute and return the score for a match with e errors and x location.
      // Accesses loc and pattern through being a closure.

      function match_bitapScore_(e, x) {
        var accuracy = e / pattern.length,
          proximity = Math.abs(loc - x)

        Iif (!Match_Distance) {
          // Dodge divide by zero error.
          return proximity ? 1.0 : accuracy
        }
        return accuracy + proximity / Match_Distance
      }

      var score_threshold = Match_Threshold, // Highest score beyond which we give up.
        best_loc = text.indexOf(pattern, loc) // Is there a nearby exact match? (speedup)

      if (best_loc != -1) {
        score_threshold = Math.min(match_bitapScore_(0, best_loc), score_threshold)
        // What about in the other direction? (speedup)
        best_loc = text.lastIndexOf(pattern, loc + pattern.length)

        if (best_loc != -1) {
          score_threshold = Math.min(match_bitapScore_(0, best_loc), score_threshold)
        }
      }

      // Initialise the bit arrays.
      var matchmask = 1 << (pattern.length - 1)
      best_loc = -1

      var bin_min, bin_mid
      var bin_max = pattern.length + text.length
      var last_rd
      for (var d = 0; d < pattern.length; d++) {
        // Scan for the best match; each iteration allows for one more error.
        // Run a binary search to determine how far from 'loc' we can stray at this
        // error level.
        bin_min = 0
        bin_mid = bin_max
        while (bin_min < bin_mid) {
          if (match_bitapScore_(d, loc + bin_mid) <= score_threshold) {
            bin_min = bin_mid
          } else {
            bin_max = bin_mid
          }
          bin_mid = Math.floor((bin_max - bin_min) / 2 + bin_min)
        }
        // Use the result from this iteration as the maximum for the next.
        bin_max = bin_mid
        var start = Math.max(1, loc - bin_mid + 1)
        var finish = Math.min(loc + bin_mid, text.length) + pattern.length

        var rd = Array(finish + 2)
        rd[finish + 1] = (1 << d) - 1
        for (var j = finish; j >= start; j--) {
          // The alphabet (s) is a sparse hash, so the following line generates
          // warnings.
          var charMatch = s[text.charAt(j - 1)]
          if (d === 0) {
            // First pass: exact match.
            rd[j] = ((rd[j + 1] << 1) | 1) & charMatch
          } else {
            // Subsequent passes: fuzzy match.
            rd[j] = (((rd[j + 1] << 1) | 1) & charMatch) | (((last_rd[j + 1] | last_rd[j]) << 1) | 1) | last_rd[j + 1]
          }
          if (rd[j] & matchmask) {
            var score = match_bitapScore_(d, j - 1)
            // This match will almost certainly be better than any existing match.
            // But check anyway.
            Eif (score <= score_threshold) {
              // Told you so.
              score_threshold = score
              best_loc = j - 1
              if (best_loc > loc) {
                // When passing loc, don't exceed our current distance from loc.
                start = Math.max(1, 2 * loc - best_loc)
              } else {
                // Already passed loc, downhill from here on in.
                break
              }
            }
          }
        }
        // No hope for a (better) match at greater error levels.
        if (match_bitapScore_(d + 1, loc) > score_threshold) {
          break
        }
        last_rd = rd
      }

      return best_loc < 0 ? false : true
    }