""" findmax(s, itr, dist::StringDistance; min_score = 0.0) -> (x, index) `findmax` returns the value and index of the element of `itr` that has the highest similarity score with `s` according to the distance `dist`. It returns `(nothing, nothing)` if none of the elements has a similarity score higher or equal to `min_score` (default to 0.0). It is particularly optimized for [`Levenshtein`](@ref) and [`DamerauLevenshtein`](@ref) distances (as well as their modifications via [`Partial`](@ref), [`TokenSort`](@ref), [`TokenSet`](@ref), or [`TokenMax`](@ref)). ### Examples ```julia-repl julia> using StringDistances julia> s = "Newark" julia> iter = ["New York", "Princeton", "San Francisco"] julia> findmax(s, iter, Levenshtein()) ("NewYork", 1) julia> findmax(s, iter, Levenshtein(); min_score = 0.9) (nothing, nothing) ``` """ function Base.findmax(s, itr, dist::StringDistance; min_score = 0.0) min_score_atomic = Threads.Atomic{typeof(min_score)}(min_score) scores = [0.0 for _ in 1:Threads.nthreads()] is = [0 for _ in 1:Threads.nthreads()] # need collect since @threads requires a length method Threads.@threads for i in collect(eachindex(itr)) score = compare(s, itr[i], dist; min_score = min_score_atomic[]) score_old = Threads.atomic_max!(min_score_atomic, score) if score >= score_old scores[Threads.threadid()] = score is[Threads.threadid()] = i end end imax = is[argmax(scores)] imax == 0 ? (nothing, nothing) : (itr[imax], imax) end """ findall(s, itr , dist::StringDistance; min_score = 0.8) `findall` returns the vector of indices for elements of `itr` that have a similarity score higher or equal than `min_score` according to the distance `dist`. If there are no such elements, return an empty array. It is particularly optimized for [`Levenshtein`](@ref) and [`DamerauLevenshtein`](@ref) distances (as well as their modifications via `Partial`, `TokenSort`, `TokenSet`, or `TokenMax`). ### Examples ```julia-repl julia> using StringDistances julia> s = "Newark" julia> iter = ["Newwark", "Princeton", "San Francisco"] julia> findall(s, iter, Levenshtein()) 1-element Array{Int64,1}: 1 julia> findall(s, iter, Levenshtein(); min_score = 0.9) 0-element Array{Int64,1} ``` """ function Base.findall(s, itr, dist::StringDistance; min_score = 0.8) out = [Int[] for _ in 1:Threads.nthreads()] # need collect since @threads requires a length method Threads.@threads for i in collect(eachindex(itr)) score = compare(s, itr[i], dist; min_score = min_score) if score >= min_score push!(out[Threads.threadid()], i) end end vcat(out...) end