62 lines
1.6 KiB
V
62 lines
1.6 KiB
V
module strings
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#-js
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// use levenshtein distance algorithm to calculate
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// the distance between between two strings (lower is closer)
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pub fn levenshtein_distance(a, b string) int {
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mut f := [0].repeat2(b.len+1)
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for ca in a {
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mut j := 1
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mut fj1 := f[0]
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f[0]++
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for cb in b {
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mut mn := if f[j]+1 <= f[j-1]+1 { f[j]+1 } else { f[j-1]+1 }
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if cb != ca {
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mn = if mn <= fj1+1 { mn } else { fj1+1 }
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} else {
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mn = if mn <= fj1 { mn } else { fj1 }
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}
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fj1 = f[j]
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f[j] = mn
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j++
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}
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}
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return f[f.len-1]
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}
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// use levenshtein distance algorithm to calculate
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// how similar two strings are as a percentage (higher is closer)
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pub fn levenshtein_distance_percentage(a, b string) f32 {
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d := levenshtein_distance(a, b)
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l := if a.len >= b.len { a.len } else { b.len }
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return (1.00 - f32(d)/f32(l)) * 100.00
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}
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// implementation of Sørensen–Dice coefficient.
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// find the similarity between two strings.
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// returns f64 between 0.0 (not similar) and 1.0 (exact match).
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pub fn dice_coefficient(s1, s2 string) f32 {
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if s1.len == 0 || s2.len == 0 { return 0.0 }
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if s1 == s2 { return 1.0 }
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if s1.len < 2 || s2.len < 2 { return 0.0 }
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mut first_bigrams := map[string]int
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for i := 0; i < s1.len-1; i++ {
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a := s1[i]
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b := s1[i+1]
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bigram := (a+b).str()
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first_bigrams[bigram] = if bigram in first_bigrams { first_bigrams[bigram]+1 } else { 1 }
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}
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mut intersection_size := 0
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for i := 0; i < s2.len-1; i++ {
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a := s2[i]
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b := s2[i+1]
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bigram := (a+b).str()
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count := if bigram in first_bigrams { first_bigrams[bigram] } else { 0 }
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if count > 0 {
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intersection_size++
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}
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}
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return (2.0 * intersection_size) / (f32(s1.len) + f32(s2.len) - 2)
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}
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