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require 'json'
class SparseVector < Hash
def initialize arg=nil
super
self.default = 0
if arg.is_a? Array
from_a arg
elsif arg.is_a? Hash
from_h arg
elsif arg.is_a? String
from_s arg
end
end
def from_a a
a.each_with_index { |i,j| self[j] = i }
end
def self.from_a a
v = SparseVector.new
v.from_a a
return v
end
def to_h
h = {}
self.each_pair { |k,v| h[k] = v }
return h
end
def from_h h
h.each_pair { |k,v| self[k] = v }
end
def self.from_h h
v = SparseVector.new
v.from_h h
return v
end
def from_s s
from_h eval(s.strip)
end
def self.from_s s
v = SparseVector.new
v.from_s s
return v
end
def to_kv sep='=', join=' '
a = []
self.each_pair { |k,v|
a << "#{k}#{sep}#{v}"
}
return a.join join
end
def from_kv s, sep='=', join=/\s/
s.strip.split(join).each { |i|
k,v = i.split(sep)
self[k] = v.to_f
}
end
def self.from_kv s, sep='=', join=/\s/
v = SparseVector.new
v.from_kv s, sep, join
return v
end
def to_json
JSON.dump self.to_h
end
def from_json s
from_h JSON.load(s)
end
def self.from_json s
v = SparseVector.new
v.from_json s
return v
end
def from_file fn, sep='='
f = ReadFile.new(fn)
while line = f.gets
key, value = line.strip.split sep
value = value.to_f
self[key] = value
end
end
def self.from_file fn, sep='='
v = SparseVector.new
v.from_file fn, sep
return v
end
def join_keys other
self.keys + other.keys
end
def sum
self.values.inject(:+)
end
def approx_eql? other, p=10**-10
return false if !other
return false if other.size!=self.size
return false if other.keys.sort!=self.keys.sort
self.keys.each { |k|
return false if (self[k]-other[k]).abs>p
}
return true
end
def average
self.sum/self.size.to_f
end
def variance
avg = self.average
var = 0.0
self.values.each { |i| var += (avg - i)**2 }
return var
end
def stddev
Math.sqrt self.variance
end
def dot other
sum = 0.0
self.each_pair { |k,v| sum += v * other[k] }
return sum
end
def zeros n
(0).upto(n-1) { |i| self[i] = 0.0 }
end
def magnitude
Math.sqrt self.values.inject { |sum,i| sum+i**2 }
end
def cosinus_sim other
self.dot(other)/(self.magnitude*other.magnitude)
end
def euclidean_dist other
dims = [self.keys, other.keys].flatten.uniq
sum = 0.0
dims.each { |d| sum += (self[d] - other[d])**2 }
return Math.sqrt(sum)
end
def + other
new = SparseVector.new
join_keys(other).each { |k|
new[k] = self[k]+other[k]
}
return new
end
def - other
new = SparseVector.new
join_keys(other).each { |k|
new[k] = self[k]-other[k]
}
return new
end
def * scalar
raise ArgumentError, "Arg is not numeric #{scalar}" unless scalar.is_a? Numeric
new = SparseVector.new
self.keys.each { |k|
new[k] = self[k] * scalar
}
return new
end
def / scalar
raise ArgumentError, "Arg is not numeric #{scalar}" unless scalar.is_a? Numeric
new = SparseVector.new
self.keys.each { |k|
new[k] = self[k] / scalar
}
return new
end
def self.mean a
mean = SparseVector.new
a.each { |i|
i.each_pair { |k,v|
mean[k] += v
}
}
n = a.size.to_f
mean.each_pair { |k,v| mean[k] = v/n }
return mean
end
def norm
return Math.sqrt(self.dot(self))
end
def unit!
n = self.norm
self.each_pair { |k,v|
self[k] /= n
}
end
def unit
v = SparseVector.new(self)
v.unit!
return v
end
end
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