| //! Levenshtein distances. |
| //! |
| //! The [Levenshtein distance] is a metric for measuring the difference between two strings. |
| //! |
| //! [Levenshtein distance]: https://en.wikipedia.org/wiki/Levenshtein_distance |
| |
| use crate::symbol::Symbol; |
| use std::cmp; |
| |
| #[cfg(test)] |
| mod tests; |
| |
| /// Finds the Levenshtein distance between two strings. |
| /// |
| /// Returns None if the distance exceeds the limit. |
| pub fn lev_distance(a: &str, b: &str, limit: usize) -> Option<usize> { |
| let n = a.chars().count(); |
| let m = b.chars().count(); |
| let min_dist = if n < m { m - n } else { n - m }; |
| |
| if min_dist > limit { |
| return None; |
| } |
| if n == 0 || m == 0 { |
| return (min_dist <= limit).then_some(min_dist); |
| } |
| |
| let mut dcol: Vec<_> = (0..=m).collect(); |
| |
| for (i, sc) in a.chars().enumerate() { |
| let mut current = i; |
| dcol[0] = current + 1; |
| |
| for (j, tc) in b.chars().enumerate() { |
| let next = dcol[j + 1]; |
| if sc == tc { |
| dcol[j + 1] = current; |
| } else { |
| dcol[j + 1] = cmp::min(current, next); |
| dcol[j + 1] = cmp::min(dcol[j + 1], dcol[j]) + 1; |
| } |
| current = next; |
| } |
| } |
| |
| (dcol[m] <= limit).then_some(dcol[m]) |
| } |
| |
| /// Provides a word similarity score between two words that accounts for substrings being more |
| /// meaningful than a typical Levenshtein distance. The lower the score, the closer the match. |
| /// 0 is an identical match. |
| /// |
| /// Uses the Levenshtein distance between the two strings and removes the cost of the length |
| /// difference. If this is 0 then it is either a substring match or a full word match, in the |
| /// substring match case we detect this and return `1`. To prevent finding meaningless substrings, |
| /// eg. "in" in "shrink", we only perform this subtraction of length difference if one of the words |
| /// is not greater than twice the length of the other. For cases where the words are close in size |
| /// but not an exact substring then the cost of the length difference is discounted by half. |
| /// |
| /// Returns `None` if the distance exceeds the limit. |
| pub fn lev_distance_with_substrings(a: &str, b: &str, limit: usize) -> Option<usize> { |
| let n = a.chars().count(); |
| let m = b.chars().count(); |
| |
| // Check one isn't less than half the length of the other. If this is true then there is a |
| // big difference in length. |
| let big_len_diff = (n * 2) < m || (m * 2) < n; |
| let len_diff = if n < m { m - n } else { n - m }; |
| let lev = lev_distance(a, b, limit + len_diff)?; |
| |
| // This is the crux, subtracting length difference means exact substring matches will now be 0 |
| let score = lev - len_diff; |
| |
| // If the score is 0 but the words have different lengths then it's a substring match not a full |
| // word match |
| let score = if score == 0 && len_diff > 0 && !big_len_diff { |
| 1 // Exact substring match, but not a total word match so return non-zero |
| } else if !big_len_diff { |
| // Not a big difference in length, discount cost of length difference |
| score + (len_diff + 1) / 2 |
| } else { |
| // A big difference in length, add back the difference in length to the score |
| score + len_diff |
| }; |
| |
| (score <= limit).then_some(score) |
| } |
| |
| /// Finds the best match for given word in the given iterator where substrings are meaningful. |
| /// |
| /// A version of [`find_best_match_for_name`] that uses [`lev_distance_with_substrings`] as the score |
| /// for word similarity. This takes an optional distance limit which defaults to one-third of the |
| /// given word. |
| /// |
| /// Besides the modified Levenshtein, we use case insensitive comparison to improve accuracy |
| /// on an edge case with a lower(upper)case letters mismatch. |
| pub fn find_best_match_for_name_with_substrings( |
| candidates: &[Symbol], |
| lookup: Symbol, |
| dist: Option<usize>, |
| ) -> Option<Symbol> { |
| find_best_match_for_name_impl(true, candidates, lookup, dist) |
| } |
| |
| /// Finds the best match for a given word in the given iterator. |
| /// |
| /// As a loose rule to avoid the obviously incorrect suggestions, it takes |
| /// an optional limit for the maximum allowable edit distance, which defaults |
| /// to one-third of the given word. |
| /// |
| /// Besides Levenshtein, we use case insensitive comparison to improve accuracy |
| /// on an edge case with a lower(upper)case letters mismatch. |
| pub fn find_best_match_for_name( |
| candidates: &[Symbol], |
| lookup: Symbol, |
| dist: Option<usize>, |
| ) -> Option<Symbol> { |
| find_best_match_for_name_impl(false, candidates, lookup, dist) |
| } |
| |
| #[cold] |
| fn find_best_match_for_name_impl( |
| use_substring_score: bool, |
| candidates: &[Symbol], |
| lookup: Symbol, |
| dist: Option<usize>, |
| ) -> Option<Symbol> { |
| let lookup = lookup.as_str(); |
| let lookup_uppercase = lookup.to_uppercase(); |
| |
| // Priority of matches: |
| // 1. Exact case insensitive match |
| // 2. Levenshtein distance match |
| // 3. Sorted word match |
| if let Some(c) = candidates.iter().find(|c| c.as_str().to_uppercase() == lookup_uppercase) { |
| return Some(*c); |
| } |
| |
| let mut dist = dist.unwrap_or_else(|| cmp::max(lookup.len(), 3) / 3); |
| let mut best = None; |
| for c in candidates { |
| match if use_substring_score { |
| lev_distance_with_substrings(lookup, c.as_str(), dist) |
| } else { |
| lev_distance(lookup, c.as_str(), dist) |
| } { |
| Some(0) => return Some(*c), |
| Some(d) => { |
| dist = d - 1; |
| best = Some(*c); |
| } |
| None => {} |
| } |
| } |
| if best.is_some() { |
| return best; |
| } |
| |
| find_match_by_sorted_words(candidates, lookup) |
| } |
| |
| fn find_match_by_sorted_words(iter_names: &[Symbol], lookup: &str) -> Option<Symbol> { |
| iter_names.iter().fold(None, |result, candidate| { |
| if sort_by_words(candidate.as_str()) == sort_by_words(lookup) { |
| Some(*candidate) |
| } else { |
| result |
| } |
| }) |
| } |
| |
| fn sort_by_words(name: &str) -> String { |
| let mut split_words: Vec<&str> = name.split('_').collect(); |
| // We are sorting primitive &strs and can use unstable sort here. |
| split_words.sort_unstable(); |
| split_words.join("_") |
| } |