module strings @[inline] fn imin(x u16, y u16) u16 { return if x < y { x } else { y } } // levenshtein_distance uses the Levenshtein Distance algorithm to calculate // the distance between between two strings `a` and `b` (lower is closer). @[direct_array_access] pub fn levenshtein_distance(a string, b string) int { if a.len == 0 { return b.len } if b.len == 0 { return a.len } if a == b { return 0 } mut row := []u16{len: a.len + 1, init: u16(index)} for i := 1; i < b.len; i++ { mut prev := u16(i) for j := 1; j < a.len; j++ { mut current := row[j - 1] // match if b[i - 1] != a[j - 1] { // insertion, substitution, deletion current = imin(imin(row[j - 1] + 1, prev + 1), row[j] + 1) } row[j - 1] = prev prev = current } row[a.len] = prev } return row[a.len] } // levenshtein_distance_percentage uses the Levenshtein Distance algorithm to calculate // how similar two strings are as a percentage (higher is closer). pub fn levenshtein_distance_percentage(a string, b string) f32 { d := levenshtein_distance(a, b) l := if a.len >= b.len { a.len } else { b.len } return (1.00 - f32(d) / f32(l)) * 100.00 } // dice_coefficient implements the Sørensen–Dice coefficient. // It finds the similarity between two strings, and returns a coefficient // between 0.0 (not similar) and 1.0 (exact match). pub fn dice_coefficient(s1 string, s2 string) f32 { if s1.len == 0 || s2.len == 0 { return 0.0 } if s1 == s2 { return 1.0 } if s1.len < 2 || s2.len < 2 { return 0.0 } a := if s1.len > s2.len { s1 } else { s2 } b := if a == s1 { s2 } else { s1 } mut first_bigrams := map[string]int{} for i in 0 .. a.len - 1 { bigram := a[i..i + 2] q := if bigram in first_bigrams { first_bigrams[bigram] + 1 } else { 1 } first_bigrams[bigram] = q } mut intersection_size := 0 for i in 0 .. b.len - 1 { bigram := b[i..i + 2] count := if bigram in first_bigrams { first_bigrams[bigram] } else { 0 } if count > 0 { first_bigrams[bigram] = count - 1 intersection_size++ } } return (2.0 * f32(intersection_size)) / (f32(a.len) + f32(b.len) - 2) }