129 lines
3.5 KiB
Julia
Executable File
129 lines
3.5 KiB
Julia
Executable File
"""
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Partial(dist)
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Creates the `Partial{dist}` distance.
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`Partial{dist}` returns the minimum distance between the shorter string and substrings of the longer string (with length equal to the shorter stirng)
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See http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/
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### Examples
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```julia-repl
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julia> s1 = "New York Mets vs Atlanta Braves"
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julia> s2 = "Atlanta Braves vs New York Mets"
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julia> Partial(RatcliffObershelp())(s1, s2)
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0.5483870967741935
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```
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"""
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struct Partial{S <: SemiMetric} <: SemiMetric
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dist::S
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end
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function (dist::Partial)(s1, s2)
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((s1 === missing) | (s2 === missing)) && return missing
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s1, s2 = reorder(s1, s2)
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len1, len2 = length(s1), length(s2)
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out = dist.dist(s1, s2)
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((len1 == 0) | (len1 == len2)) && return out
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for x in qgrams(s2, len1)
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curr = dist.dist(s1, x)
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out = min(out, curr)
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end
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return out
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end
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function (dist::Partial{RatcliffObershelp})(s1, s2)
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((s1 === missing) | (s2 === missing)) && return missing
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s1, s2 = reorder(s1, s2)
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len1, len2 = length(s1), length(s2)
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len1 == len2 && return dist.dist(s1, s2)
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out = 1.0
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for r in matching_blocks(s1, s2)
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# Make sure the substring of s2 has length len1
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s2_start = r[2] - r[1] + 1
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s2_end = s2_start + len1 - 1
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if s2_start < 1
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s2_end += 1 - s2_start
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s2_start += 1 - s2_start
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elseif s2_end > len2
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s2_start += len2 - s2_end
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s2_end += len2 - s2_end
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end
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curr = dist.dist(s1, _slice(s2, s2_start - 1, s2_end))
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out = min(out, curr)
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end
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return out
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end
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"""
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TokenSort(dist)
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Creates the `TokenSort{dist}` distance.
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`TokenSort{dist}` returns the distance between strings after reording words alphabetically.
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See http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/
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It is only defined on AbstractStrings.
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### Examples
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```julia-repl
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julia> s1 = "New York Mets vs Atlanta Braves"
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julia> s1 = "New York Mets vs Atlanta Braves"
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julia> s2 = "Atlanta Braves vs New York Mets"
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julia> TokenSort(RatcliffObershelp())(s1, s2)
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0.0
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```
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"""
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struct TokenSort{S <: SemiMetric} <: SemiMetric
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dist::S
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end
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function (dist::TokenSort)(s1::Union{AbstractString, Missing}, s2::Union{AbstractString, Missing})
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((s1 === missing) | (s2 === missing)) && return missing
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s1 = join(sort!(split(s1)), " ")
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s2 = join(sort!(split(s2)), " ")
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out = dist.dist(s1, s2)
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end
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"""
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TokenSet(dist)
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Creates the `TokenSet{dist}` distance.
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`TokenSet{dist}` returns the minimum the distances between:
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[SORTED_INTERSECTION]
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[SORTED_INTERSECTION] + [SORTED_REST_OF_STRING1]
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[SORTED_INTERSECTION] + [SORTED_REST_OF_STRING2]
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See: http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/
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It is only defined on AbstractStrings.
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### Examples
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```julia-repl
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julia> s1 = "New York Mets vs Atlanta"
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julia> s2 = "Atlanta Braves vs New York Mets"
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julia> TokenSet(RatcliffObershelp())(s1, s2)
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0.0
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```
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"""
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struct TokenSet{S <: SemiMetric} <: SemiMetric
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dist::S
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end
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function (dist::TokenSet)(s1::Union{AbstractString, Missing}, s2::Union{AbstractString, Missing})
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((s1 === missing) | (s2 === missing)) && return missing
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v1 = unique!(sort!(split(s1)))
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v2 = unique!(sort!(split(s2)))
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v0 = intersect(v1, v2)
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s0 = join(v0, " ")
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s1 = join(v1, " ")
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s2 = join(v2, " ")
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isempty(s0) && return dist.dist(s1, s2)
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score_01 = dist.dist(s0, s1)
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score_02 = dist.dist(s0, s2)
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score_12 = dist.dist(s1, s2)
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min(score_01, score_02, score_12)
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end
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