62 lines
1.7 KiB
V
62 lines
1.7 KiB
V
module strings
|
||
|
||
#-js
|
||
|
||
// use levenshtein distance algorithm to calculate
|
||
// the distance between between two strings (lower is closer)
|
||
pub fn levenshtein_distance(a, b string) int {
|
||
mut f := [0].repeat(b.len+1)
|
||
for ca in a {
|
||
mut j := 1
|
||
mut fj1 := f[0]
|
||
f[0]++
|
||
for cb in b {
|
||
mut mn := if f[j]+1 <= f[j-1]+1 { f[j]+1 } else { f[j-1]+1 }
|
||
if cb != ca {
|
||
mn = if mn <= fj1+1 { mn } else { fj1+1 }
|
||
} else {
|
||
mn = if mn <= fj1 { mn } else { fj1 }
|
||
}
|
||
fj1 = f[j]
|
||
f[j] = mn
|
||
j++
|
||
}
|
||
}
|
||
return f[f.len-1]
|
||
}
|
||
|
||
// use levenshtein distance algorithm to calculate
|
||
// how similar two strings are as a percentage (higher is closer)
|
||
pub fn levenshtein_distance_percentage(a, 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
|
||
}
|
||
|
||
// implementation of Sørensen–Dice coefficient.
|
||
// find the similarity between two strings.
|
||
// returns coefficient between 0.0 (not similar) and 1.0 (exact match).
|
||
pub fn dice_coefficient(s1, 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 := 0; i < a.len-1; i++ {
|
||
bigram := a.substr(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 := 0; i < b.len-1; i++ {
|
||
bigram := b.substr(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 * intersection_size) / (f32(a.len) + f32(b.len) - 2)
|
||
}
|