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module OpenTox
module Algorithm
class Vector
def self.dot_product(a, b)
products = a.zip(b).map{|a, b| a * b}
products.inject(0) {|s,p| s + p}
end
def self.magnitude(point)
squares = point.map{|x| x ** 2}
Math.sqrt(squares.inject(0) {|s, c| s + c})
end
end
class Similarity
def self.tanimoto fingerprints
( fingerprints[0] & fingerprints[1]).size/(fingerprints[0]|fingerprints[1]).size.to_f
end
def self.euclid fingerprints
sq = fingerprints[0].zip(fingerprints[1]).map{|a,b| (a - b) ** 2}
Math.sqrt(sq.inject(0) {|s,c| s + c})
end
# http://stackoverflow.com/questions/1838806/euclidean-distance-vs-pearson-correlation-vs-cosine-similarity
def self.cosine fingerprints
Algorithm::Vector.dot_product(fingerprints[0], fingerprints[1]) / (Algorithm::Vector.magnitude(fingerprints[0]) * Algorithm::Vector.magnitude(fingerprints[1]))
end
def self.weighted_cosine fingerprints # [a,b,weights]
a, b, w = fingerprints
dot_product = 0
magnitude_a = 0
magnitude_b = 0
(0..a.size-1).each do |i|
dot_product += w[i].abs*a[i]*b[i]
magnitude_a += w[i].abs*a[i]**2
magnitude_b += w[i].abs*b[i]**2
end
dot_product/(Math.sqrt(magnitude_a)*Math.sqrt(magnitude_b))
end
end
end
end
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