Today I am publishing an algorithm for calculating the Damerau-Levenshtein distance in F#. The Levenshtein distance is a metric that allows to measure the amount of difference between two sequences and shows how many edit operations (insert, delete, substitution) are needed to transform one sequence into the other. The Damerau-Levenshtein distance allows the transposition of two characters as an operation. It is often used for spelling corrections or to measure the variation (“edit distance”) between DNA sequences.
let damerauLevenshtein(a:'a array) (b:'a array) =
let init i j =
if j = 0 then i
elif i = 0 then j else 0
let n = a.Length + 1
let m = b.Length + 1
let d = Array2.init n m init
for i in [1..a.Length] do
for j in [1..b.Length] do
let cost =
if a.[i-1] = b.[j-1] then 0 else 1
let deletion = d.[i-1, j] + 1
let insertion = d.[i,j-1] + 1
let substitution = d.[i-1,j-1] + cost
d.[i, j] <-
deletion
|> min insertion
|> min substitution
if i > 1 && j > 1 && a.[i-1] = b.[j-2] &&
a.[i-2] = b.[j-1] then
let transposition = d.[i-2,j-2] + cost
d.[i, j] <- min d.[i,j] transposition
d.[a.Length, b.Length]
This naïve implementation needs quadratic space (O(m*n)). Since the algorithm is used to calculate the edit distance of large DNA sequences this is extremly bad. Next time I will show how we can get linear space (O(m+n)) for the algorithm.
Tags: alignment, Damerau, dna, dynamic programming, edit distance, F#, Levenshtein algorithm, Levenshtein distance