cleanups

src/StringDistances.jl

@@ -5,13 +5,24 @@ using Distances
 include("utils.jl")
 include("edit.jl")
 include("qgram.jl")
-include("modifiers.jl")
+include("normalize.jl")
 
 const StringDistance = Union{Jaro, Levenshtein, DamerauLevenshtein, RatcliffObershelp, QGramDistance, Winkler, Partial, TokenSort, TokenSet, TokenMax, Normalize}
 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")
 

src/edit.jl

@@ -24,7 +24,6 @@ function (dist::Jaro)(s1, s2)
     len2 == 0 && return 0.0
     maxdist = max(0, div(len2, 2) - 1)
     flag = fill(false, len2)
-    prevstate1 = firstindex(s1)
     ch1_match = Vector{eltype(s1)}(undef, len1)
     #  m counts number matching characters
     m = 0 

src/find.jl

@@ -1,18 +1,3 @@
-"""
-    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)
-
-
 """
     findmax(s, itr, dist::StringDistance; min_score = 0.0) -> (x, index)