Struct str_distance::levenshtein::DamerauLevenshtein

pub struct DamerauLevenshtein { /* fields omitted */ }

Specify a maximum distance. Specifying a maximum distance allows short circuit exit after exceeding the maximum distance and less cell evaluation. It essentially changes the time complexity from being the product of the two string lengths to being just the length of the shorter string

See http://blog.softwx.net/2015/01/optimizing-damerau-levenshtein_15.html Note that this is based on Sten Hjelmqvist's "Fast, memory efficient" algorithm, described at http://www.codeproject.com/Articles/13525/Fast-memory-efficient-Levenshtein-algorithm. This version differs by including some optimizations, and extending it to the Damerau- Levenshtein algorithm. Note that this is the simpler and faster optimal string alignment (aka restricted edit) distance that difers slightly from the classic Damerau-Levenshtein algorithm by imposing the restriction that no substring is edited more than once. So for example, "CA" to "ABC" has an edit distance of 2 by a complete application of Damerau-Levenshtein, but a distance of 3 by this method that uses the optimal string alignment algorithm. See wikipedia article for more detail on this distinction.

Methods

impl DamerauLevenshtein

pub fn with_max_distance(max_distance: usize) -> Self

Trait Implementations

impl Clone for DamerauLevenshtein

fn clone(&self) -> DamerauLevenshtein

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for DamerauLevenshtein

fn fmt(&self, f: &mut Formatter) -> Result

Formats the value using the given formatter.

impl Default for DamerauLevenshtein

fn default() -> DamerauLevenshtein

Returns the "default value" for a type.

impl DistanceMetric for DamerauLevenshtein

type Dist = DistanceValue

Represents the data type in which this distance is evaluated.

fn distance<S, T>(&self, a: S, b: T) -> Self::Dist where
    S: IntoIterator,
    T: IntoIterator,
    <S as IntoIterator>::IntoIter: Clone,
    <T as IntoIterator>::IntoIter: Clone,
    <S as IntoIterator>::Item: PartialEq + PartialEq<<T as IntoIterator>::Item>,
    <T as IntoIterator>::Item: PartialEq, 

Generic implementation of the metric.

fn str_distance<S, T>(&self, s1: S, s2: T) -> Self::Dist where
    S: AsRef<str>,
    T: AsRef<str>, 

Evaluates the distance between two str.

fn normalized<S, T>(&self, a: S, b: T) -> f64 where
    S: IntoIterator,
    T: IntoIterator,
    <S as IntoIterator>::IntoIter: Clone,
    <T as IntoIterator>::IntoIter: Clone,
    <S as IntoIterator>::Item: PartialEq + PartialEq<<T as IntoIterator>::Item>,
    <T as IntoIterator>::Item: PartialEq, 

Evaluates the normalized distance between two strings A value of '0.0' corresponds to the "zero distance", both strings are considered equal by means of the metric, whereas a value of '1.0' corresponds to the maximum distance that can exist between the strings.

fn str_normalized<S, T>(&self, a: S, b: T) -> f64 where
    S: AsRef<str>,
    T: AsRef<str>, 

Convenience normalization for str types.