minor style fixes

src/LM/langmodel.jl

@@ -99,20 +99,18 @@ To get probability of word given that context
 In other words, for given context calculate frequency distribution of word
   
 """
-function prob(m::Langmodel, templ_lm::DefaultDict, word, context=nothing)
-    if context == nothing || context == ""
-        return(1/float(length(templ_lm))) #provide distribution 
-    else
-        accum = templ_lm[context]
-    end
+function prob(m::Langmodel, templ_lm::DefaultDict, word, context=nothing)::Float64
+    (isnothing(context) || isempty(context)) && return 1.0/length(templ_lm) #provide distribution
+
+    accum = templ_lm[context]
     s = float(sum(accum)) 
     for (text, count) in accum
         if text == word
             return(float(count) / s)
         end
     end
     if context in keys(m.vocab.vocab)
-        return(0)
+        return 0.0
     end
     return(Inf)
 end
@@ -186,9 +184,8 @@ depending upon the sub-Type
         
 """
 function score(m::InterpolatedLanguageModel, temp_lm::DefaultDict, word, context=nothing)
-    if context == nothing || context == ""
-        return prob(m, temp_lm, word, context)
-    end
+    (isnothing(context) || isempty(context)) && return prob(m, temp_lm, word)
+
     if context in keys(temp_lm)
         alpha,gamma = alpha_gammma(m, temp_lm, word, context)
         return (alpha + gamma*score(m, temp_lm, word, context_reduce(context)))
@@ -242,5 +239,3 @@ function alpha_gammma(m::KneserNeyInterpolated, templ_lm::DefaultDict, word, con
     gamma = (m.discount * count_non_zero_vals(accum) /s)
     return alpha, gamma
 end
-
-

src/deprecations.jl

@@ -1,7 +1,7 @@
 
 ## Deprecations for Languages
 
-function WordTokenizers.tokenize(::Type{S}, s::T) where {S <: Language, T <: AbstractString}
+function tokenize(::Type{S}, s::T) where {S <: Language, T <: AbstractString}
     depwarn("Use of Languages as types is deprecated. Use instances.",  Symbol(S))
     tokenize(S(), s)
 end

src/tokenizer.jl

@@ -16,7 +16,7 @@ julia> tokenize(Languages.English(), "Too foo words!")
 
 See also: [`sentence_tokenize`](@ref)
 """
-WordTokenizers.tokenize(lang::S, s::T) where {S <: Language, T <: AbstractString} = WordTokenizers.tokenize(s)
+tokenize(lang::S, s::T) where {S <: Language, T <: AbstractString} = WordTokenizers.tokenize(s)
 
 
 """