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Levenshtein Distance algorithm
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/* eslint-disable */ | |
/** | |
Based on https://github.com/ka-weihe/fastest-levenshtein | |
MIT License | |
Copyright (c) 2020 Kasper Unn Weihe | |
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. | |
*/ | |
var peq = new Uint32Array(0x10000) | |
function myers_32(a, b) { | |
var n = a.length | |
var m = b.length | |
var lst = 1 << (n - 1) | |
var pv = -1 | |
var mv = 0 | |
var sc = n | |
var i = n | |
while (i--) { | |
peq[a.charCodeAt(i)] |= 1 << i | |
} | |
for (i = 0; i < m; i++) { | |
var eq = peq[b.charCodeAt(i)] | |
var xv = eq | mv | |
eq |= ((eq & pv) + pv) ^ pv | |
mv |= ~(eq | pv) | |
pv &= eq | |
if (mv & lst) { | |
sc++ | |
} | |
if (pv & lst) { | |
sc-- | |
} | |
mv = (mv << 1) | 1 | |
pv = (pv << 1) | ~(xv | mv) | |
mv &= xv | |
} | |
i = n | |
while (i--) { | |
peq[a.charCodeAt(i)] = 0 | |
} | |
return sc | |
} | |
function myers_x(a, b) { | |
var n = a.length | |
var m = b.length | |
var mhc = [] | |
var phc = [] | |
var hsize = Math.ceil(n / 32) | |
var vsize = Math.ceil(m / 32) | |
var score = m | |
for (var i = 0; i < hsize; i++) { | |
phc[i] = -1 | |
mhc[i] = 0 | |
} | |
var j = 0 | |
for (; j < vsize - 1; j++) { | |
var mv = 0 | |
var pv = -1 | |
var start = j * 32 | |
var end = Math.min(32, m) + start | |
for (var k = start; k < end; k++) { | |
peq[b.charCodeAt(k)] |= 1 << k | |
} | |
score = m | |
for (var i = 0; i < n; i++) { | |
var eq = peq[a.charCodeAt(i)] | |
var pb = (phc[(i / 32) | 0] >>> i) & 1 | |
var mb = (mhc[(i / 32) | 0] >>> i) & 1 | |
var xv = eq | mv | |
var xh = ((((eq | mb) & pv) + pv) ^ pv) | eq | mb | |
var ph = mv | ~(xh | pv) | |
var mh = pv & xh | |
if ((ph >>> 31) ^ pb) { | |
phc[(i / 32) | 0] ^= 1 << i | |
} | |
if ((mh >>> 31) ^ mb) { | |
mhc[(i / 32) | 0] ^= 1 << i | |
} | |
ph = (ph << 1) | pb | |
mh = (mh << 1) | mb | |
pv = mh | ~(xv | ph) | |
mv = ph & xv | |
} | |
for (var k = start; k < end; k++) { | |
peq[b.charCodeAt(k)] = 0 | |
} | |
} | |
var mv = 0 | |
var pv = -1 | |
var start = j * 32 | |
var end = Math.min(32, m - start) + start | |
for (var k = start; k < end; k++) { | |
peq[b.charCodeAt(k)] |= 1 << k | |
} | |
score = m | |
for (var i = 0; i < n; i++) { | |
var eq = peq[a.charCodeAt(i)] | |
var pb = (phc[(i / 32) | 0] >>> i) & 1 | |
var mb = (mhc[(i / 32) | 0] >>> i) & 1 | |
var xv = eq | mv | |
var xh = ((((eq | mb) & pv) + pv) ^ pv) | eq | mb | |
var ph = mv | ~(xh | pv) | |
var mh = pv & xh | |
score += (ph >>> (m - 1)) & 1 | |
score -= (mh >>> (m - 1)) & 1 | |
if ((ph >>> 31) ^ pb) { | |
phc[(i / 32) | 0] ^= 1 << i | |
} | |
if ((mh >>> 31) ^ mb) { | |
mhc[(i / 32) | 0] ^= 1 << i | |
} | |
ph = (ph << 1) | pb | |
mh = (mh << 1) | mb | |
pv = mh | ~(xv | ph) | |
mv = ph & xv | |
} | |
for (var k = start; k < end; k++) { | |
peq[b.charCodeAt(k)] = 0 | |
} | |
return score | |
} | |
function levenshteinSimilarity(a, b) { | |
// Shortcutting identical strings | |
if(a === b) return 1 | |
// If the code reaches here it means the strings are different. | |
// So, if at least one of them has zero length, they are completely different, therefore the result is 0 | |
if (a.length === 0 || b.length === 0) { | |
return 0 | |
} | |
// If a is longer than b, we switch the variables to make sure b is always the longest one | |
if (a.length > b.length) { | |
var tmp = b | |
b = a | |
a = tmp | |
} | |
var steps = a.length <= 32 ? myers_32(a, b) : myers_x(a, b) | |
// if a and b are different, b will always be the longest string | |
var relative = steps / b.length | |
return 1 - relative | |
} | |
onmessage = function(event) { | |
var chunk = event.data.chunk | |
var destination = event.data.destination | |
var mappings = [] | |
for (var chunkIndex in chunk) { | |
var source = chunk[chunkIndex] | |
var found = destination.filter(function(destination) { | |
return destination === source | |
})[0] || undefined | |
if (found) { | |
mappings.push({ destination: found, source, similarity: 1 }) | |
} else { | |
for (var destinationIndex in destination) { | |
var found = destination[destinationIndex] | |
var similarity = levenshteinSimilarity(source, found) | |
if (similarity >= 0.5) { | |
mappings.push({ destination: found, source, similarity }) | |
break | |
} | |
} | |
} | |
} | |
postMessage(mappings) | |
} |
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