1
0
Fork 0
mirror of https://github.com/Luzifer/ansible-role-version.git synced 2024-12-23 19:11:20 +00:00
ansible-role-version/vendor/github.com/sergi/go-diff/diffmatchpatch/match.go

161 lines
4.7 KiB
Go
Raw Normal View History

// Copyright (c) 2012-2016 The go-diff authors. All rights reserved.
// https://github.com/sergi/go-diff
// See the included LICENSE file for license details.
//
// go-diff is a Go implementation of Google's Diff, Match, and Patch library
// Original library is Copyright (c) 2006 Google Inc.
// http://code.google.com/p/google-diff-match-patch/
package diffmatchpatch
import (
"math"
)
// MatchMain locates the best instance of 'pattern' in 'text' near 'loc'.
// Returns -1 if no match found.
func (dmp *DiffMatchPatch) MatchMain(text, pattern string, loc int) int {
// Check for null inputs not needed since null can't be passed in C#.
loc = int(math.Max(0, math.Min(float64(loc), float64(len(text)))))
if text == pattern {
// Shortcut (potentially not guaranteed by the algorithm)
return 0
} else if len(text) == 0 {
// Nothing to match.
return -1
} else if loc+len(pattern) <= len(text) && text[loc:loc+len(pattern)] == pattern {
// Perfect match at the perfect spot! (Includes case of null pattern)
return loc
}
// Do a fuzzy compare.
return dmp.MatchBitap(text, pattern, loc)
}
// MatchBitap locates the best instance of 'pattern' in 'text' near 'loc' using the Bitap algorithm.
// Returns -1 if no match was found.
func (dmp *DiffMatchPatch) MatchBitap(text, pattern string, loc int) int {
// Initialise the alphabet.
s := dmp.MatchAlphabet(pattern)
// Highest score beyond which we give up.
scoreThreshold := dmp.MatchThreshold
// Is there a nearby exact match? (speedup)
bestLoc := indexOf(text, pattern, loc)
if bestLoc != -1 {
scoreThreshold = math.Min(dmp.matchBitapScore(0, bestLoc, loc,
pattern), scoreThreshold)
// What about in the other direction? (speedup)
bestLoc = lastIndexOf(text, pattern, loc+len(pattern))
if bestLoc != -1 {
scoreThreshold = math.Min(dmp.matchBitapScore(0, bestLoc, loc,
pattern), scoreThreshold)
}
}
// Initialise the bit arrays.
matchmask := 1 << uint((len(pattern) - 1))
bestLoc = -1
var binMin, binMid int
binMax := len(pattern) + len(text)
lastRd := []int{}
for d := 0; d < len(pattern); 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.
binMin = 0
binMid = binMax
for binMin < binMid {
if dmp.matchBitapScore(d, loc+binMid, loc, pattern) <= scoreThreshold {
binMin = binMid
} else {
binMax = binMid
}
binMid = (binMax-binMin)/2 + binMin
}
// Use the result from this iteration as the maximum for the next.
binMax = binMid
start := int(math.Max(1, float64(loc-binMid+1)))
finish := int(math.Min(float64(loc+binMid), float64(len(text))) + float64(len(pattern)))
rd := make([]int, finish+2)
rd[finish+1] = (1 << uint(d)) - 1
for j := finish; j >= start; j-- {
var charMatch int
if len(text) <= j-1 {
// Out of range.
charMatch = 0
} else if _, ok := s[text[j-1]]; !ok {
charMatch = 0
} else {
charMatch = s[text[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 | (((lastRd[j+1] | lastRd[j]) << 1) | 1) | lastRd[j+1]
}
if (rd[j] & matchmask) != 0 {
score := dmp.matchBitapScore(d, j-1, loc, pattern)
// This match will almost certainly be better than any existing match. But check anyway.
if score <= scoreThreshold {
// Told you so.
scoreThreshold = score
bestLoc = j - 1
if bestLoc > loc {
// When passing loc, don't exceed our current distance from loc.
start = int(math.Max(1, float64(2*loc-bestLoc)))
} else {
// Already passed loc, downhill from here on in.
break
}
}
}
}
if dmp.matchBitapScore(d+1, loc, loc, pattern) > scoreThreshold {
// No hope for a (better) match at greater error levels.
break
}
lastRd = rd
}
return bestLoc
}
// matchBitapScore computes and returns the score for a match with e errors and x location.
func (dmp *DiffMatchPatch) matchBitapScore(e, x, loc int, pattern string) float64 {
accuracy := float64(e) / float64(len(pattern))
proximity := math.Abs(float64(loc - x))
if dmp.MatchDistance == 0 {
// Dodge divide by zero error.
if proximity == 0 {
return accuracy
}
return 1.0
}
return accuracy + (proximity / float64(dmp.MatchDistance))
}
// MatchAlphabet initialises the alphabet for the Bitap algorithm.
func (dmp *DiffMatchPatch) MatchAlphabet(pattern string) map[byte]int {
s := map[byte]int{}
charPattern := []byte(pattern)
for _, c := range charPattern {
_, ok := s[c]
if !ok {
s[c] = 0
}
}
i := 0
for _, c := range charPattern {
value := s[c] | int(uint(1)<<uint((len(pattern)-i-1)))
s[c] = value
i++
}
return s
}