Update normalize.jl

src/normalize.jl

@@ -3,7 +3,8 @@
 """
    Normalized(dist::Union{StringSemiMetric, StringMetric})
 
-Creates a normalized distance. The normalized distance always return a Float64 between 0.0 and 1.0 (or a missing if one of the argument is missing)
+Creates a normalized distance. The normalized distance always return a Float64 between 0.0 and 1.0 (or a missing if one of the argument is missing). 
+A Normalized Distance has a keyword argument `max_dist` that defaults to 1.0. It returns 1.0 if the true distance is higher than `max_dist`.
 
 ### Examples
 ```julia-repl
@@ -20,7 +21,7 @@ struct Normalized{T <: Union{StringSemiMetric, StringMetric}} <: StringSemiMetri
 end
 Normalized(dist::Normalized) = dist
 
-# this basically says that all distances are considered to be normalized by default
+# Consider all distances to be normalized by default
 function (dist::Normalized)(s1, s2; max_dist = 1.0)
     out = dist.dist(s1, s2; max_dist = max_dist)
     max_dist !== nothing && out > max_dist && return 1.0
@@ -29,9 +30,9 @@ end
 
 function (dist::Normalized{<:Union{Hamming, DamerauLevenshtein}})(s1, s2; max_dist = 1.0)
     (s1 === missing) | (s2 === missing) && return missing
-    isempty(s1) && isempty(s2) && return 0.0
     s1, s2 = reorder(s1, s2)
     len1, len2 = length(s1), length(s2)
+    len2 == 0 && return 0.0
     out = dist.dist(s1, s2) / len2
     max_dist !== nothing && out > max_dist && return 1.0
     return out
@@ -39,9 +40,9 @@ end
 
 function (dist::Normalized{<:Union{Levenshtein, OptimalStringAlignement}})(s1, s2; max_dist = 1.0)
     (s1 === missing) | (s2 === missing) && return missing
-    isempty(s1) && isempty(s2) && return 0.0
     s1, s2 = reorder(s1, s2)
     len1, len2 = length(s1), length(s2)
+    len2 == 0 && return 0.0
     if max_dist == 1.0
         d = dist.dist(s1, s2)
     else
@@ -57,7 +58,7 @@ function (dist::Normalized{<:AbstractQGramDistance})(s1, s2; max_dist = 1.0)
     # When string length < q for qgram distance, returns s1 == s2
     s1, s2 = reorder(s1, s2)
     len1, len2 = length(s1), length(s2)
-    len1 <= dist.dist.q - 1 && return convert(Float64, s1 != s2)
+    len1 <= dist.dist.q - 1 && return Float64(s1 != s2)
     if dist.dist isa QGram
         out = dist.dist(s1, s2) / (len1 + len2 - 2 * dist.dist.q + 2)
     else