Add :mean to Arrays

mean.rb

module WhiteHat101
  module Mean
    def mean
      inject(0.0, :+) / length
    end
    alias avg mean
    alias average mean
    
    def mean_absolute_deviation
      mean = self.mean
      map {|r| (mean - r).abs }.mean
    end
    alias mad mean_absolute_deviation
    
    def standard_deviation
      mean = self.mean
      Math.sqrt inject(0.0) {|sum, x| sum + (x - mean)**2 } / self.length.to_f
    end
    def standard_deviation2
      mean = self.mean
      Math.sqrt inject(0.0) {|sum, x| sum + (x - mean)**2 } / (self.length.to_f - 1)
    end
  end
end

Array.send :include, WhiteHat101::Mean

# to work these problems
# - first, last, delta
# - first, second, last
# - first, delta, n

class Arithmetic
  attr_accessor :a1, :an, :n, :sum, :delta
  # def initialize; end
  def self.from_a1_a2_an a1, a2, an
    a = new
    a.delta_from_values 1,a1, 2,a2
    a.n_from_first_last a1, an
    a
  end
  def self.from_a1_delta_n a1, delta, n
    a = new
    a.a1 = a1
    a.delta = delta
    a.n = n
    a.an_from_a1_delta_n
    a
  end

  def delta_from_values n1, v1, n2, v2
    @delta = (v2-v1)/(n2-n1).to_f
  end
  def n_from_first_last a1, an
    raise "need delta" unless @delta
    @a1 ||= a1
    @an ||= an
    @n = ((@a1 - @an)/@delta).abs + 1
  end
  def sum
    (a1 + an)/2.0*n
  end
  def an_from_a1_delta_n
    @an = a1 + delta*(n-1)
  end
end

def d x1,y1, x2,y2
  Math.sqrt((x2-x1)**2+(y2-y1)**2)
end

def complex_distance a,ai, b,bi
  (Complex(a,ai) - Complex(b, bi)).abs
end

def eulers_method x0, y0, xN, step = 1.0, &block
  until x0 > xN
    puts "A(#{x0}) = #{y0} (step #{step})"
    y0 += step * block.call(x0, y0)
    x0 += step
  end
end

def dilate origin_x, origin_y, scale=1.0
  proc do |x,y|
    [origin_x+scale*(x-origin_x), origin_y+scale*(y-origin_y)]
  end
end
# [[2,2],[6,2],[2,5]].map &dilate(6,5,3) # => [[-6, -4], [6, -4], [-6, 5]]

Reflect over y = -x + 3

[[-2,5],[3,8],[2,6],[7,4],[7,2]].map{|x,y|[-y+3,-x+3]} # => [[-2, 5], [-5, 0], [-3, 1], [-1, -4], [1, -4]]