findmax -> findnearest

Project.toml

@@ -1,6 +1,6 @@
 name = "StringDistances"
 uuid = "88034a9c-02f8-509d-84a9-84ec65e18404"
-version = "0.8"
+version = "0.9.0"
 
 [deps]
 Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"

src/StringDistances.jl

@@ -2,31 +2,17 @@ module StringDistances
 
 using Distances
 
-include("utils.jl")
-include("edit.jl")
-include("qgram.jl")
+include("distances/utils.jl")
+include("distances/edit.jl")
+include("distances/qgram.jl")
 include("normalize.jl")
 
 const StringDistance = Union{Jaro, Levenshtein, DamerauLevenshtein, RatcliffObershelp, QGramDistance, Winkler, Partial, TokenSort, TokenSet, TokenMax, Normalize}
 # Distances API
 Distances.result_type(dist::StringDistance, s1, s2) = typeof(dist("", ""))
-
-"""
-    compare(s1, s2, dist)
-
-return a similarity score between 0 and 1 for the strings `s1` and 
-`s2` based on the distance `dist`.
-
-### Examples
-```julia-repl
-julia> compare("martha", "marhta", Levenshtein())
-0.6666666666666667
-```
-"""
-compare(s1, s2, dist::StringDistance; min_score = 0.0) = 1 - normalize(dist)(s1, s2, 1 - min_score)
-
 include("find.jl")
 
+
 ##############################################################################
 ##
 ## Export

src/find.jl

@@ -1,3 +1,18 @@
+"""
+    compare(s1, s2, dist)
+
+return a similarity score between 0 and 1 for the strings `s1` and 
+`s2` based on the distance `dist`.
+
+### Examples
+```julia-repl
+julia> compare("martha", "marhta", Levenshtein())
+0.6666666666666667
+```
+"""
+compare(s1, s2, dist::StringDistance; min_score = 0.0) = 1 - normalize(dist)(s1, s2, 1 - min_score)
+
+
 """
     findnearest(s, itr, dist::StringDistance; min_score = 0.0) -> (x, index)
 

src/normalize.jl

@@ -259,4 +259,6 @@ function (dist::Winkler)(s1, s2, max_dist = 1.0)
         out -= min(l, dist.maxlength) * dist.p * out
     end
     out > max_dist ? 1.0 : out
-end
+end
+
+