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Diffstat (limited to 'v_windows/v/vlib/strings/similarity.v')
-rw-r--r-- | v_windows/v/vlib/strings/similarity.v | 69 |
1 files changed, 69 insertions, 0 deletions
diff --git a/v_windows/v/vlib/strings/similarity.v b/v_windows/v/vlib/strings/similarity.v new file mode 100644 index 0000000..8d8de95 --- /dev/null +++ b/v_windows/v/vlib/strings/similarity.v @@ -0,0 +1,69 @@ +module strings + +// #-js +// use levenshtein distance algorithm to calculate +// the distance between between two strings (lower is closer) +pub fn levenshtein_distance(a string, b string) int { + mut f := [0].repeat(b.len + 1) + for j in 0 .. f.len { + f[j] = j + } + 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 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 +} + +// 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 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) +} |