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# lplp.rb
# norms
def l0(feature_column, n)
if feature_column.size == n then return 1 else return 0 end
end
def l1(feature_column, n=-1)
return feature_column.reduce { |sum, i| i.abs }
end
def l2(feature_column, n=-1)
return Math.sqrt feature_column.reduce { |sum, i| i**2 }
end
def linfty(feature_column, n=-1)
return feature_column.map { |i| i.abs }.max
end
# stats
def M(feature_column, n)
return feature_column.concat(0.step(n-feature_column.size-1).map{|i|0}).sort[feature_column.size/2]
end
def mean(feature_column, n)
return feature_column.reduce { |sum, i| sum+i } / n
end
# selection
def select_k(weights, normfn, n, k=10000)
weights.sort{|a,b| normfn.call(b[1], n) <=> normfn.call(a[1], n)}.each { |p|
puts "#{p[0]}\t#{mean(p[1], n)}"
k -= 1
if k == 0 then break end
}
end
def cut(weights, normfn, n, epsilon=0.0001)
weights.each { |k,v|
if normfn.call(v).abs > epsilon
puts "#{k}\t#{mean(v, n)}"
end
}
end
shard_count_key = "__SHARD_COUNT__"
STDIN.set_encoding 'utf-8'
STDOUT.set_encoding 'utf-8'
w = {}
shard_count = 0
while line = STDIN.gets
key, val = line.split /\t/
if k = shard_count_key
shard_count += 1
next
end
if w.has_key? key
w[key].push val
else
w[key] = [val]
end
end
select_k(w, method(:l1), shard_count, 100000)
def _test()
puts
w = {}
w["a"] = [1, 2, 3]
w["b"] = [1, 2]
w["c"] = [66]
w["d"] = [10, 20, 30]
n = 3
puts w.to_s
puts
puts "select_k"
puts "l0 expect ad"
select_k(w, method(:l0), n, 2)
puts "l1 expect c"
select_k(w, method(:l1), n, 1)
puts "l2 expect d"
select_k(w, method(:l2), n, 1)
puts
puts "cut"
puts "l1 expect cd"
cut(w, method(:l1), n, 7)
puts
puts "M"
a = [1,3,4,5,6]
puts a.to_s
puts M(a, 7)
puts "that's because we add missing 0s"
puts a.concat(0.step(7-a.size-1).map{|i|0}).to_s
puts
end
#_test()
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