module Measurable::Euclidean

Public Instance Methods

euclidean(u) → Float click to toggle source
euclidean(u, v) → Float

Calculate the ordinary distance between arrays u and v.

If v isn't given, calculate the Euclidean norm of u.

See: en.wikipedia.org/wiki/Euclidean_distance#N_dimensions

Arguments:

  • u -> An array of Numeric objects.

  • v -> (Optional) An array of Numeric objects.

Returns:

  • The euclidean norm of u or the euclidean distance between u and v.

Raises:

  • ArgumentError -> The sizes of u and v don't match.

# File lib/measurable/euclidean.rb, line 21
def euclidean(u, v = nil)
  Math.sqrt(self.euclidean_squared(u, v))
end
euclidean_squared(u) → Float click to toggle source
euclidean_squared(u, v) → Float

Calculate the same value as euclidean(u, v), but don't take the square root of it.

This isn't a metric in the strict sense, i.e. it doesn't respect the triangle inequality. However, the squared Euclidean distance is very useful whenever only the relative values of distances are important, for example in optimization problems.

See: en.wikipedia.org/wiki/Euclidean_distance#Squared_Euclidean_distance

Arguments:

  • u -> An array of Numeric objects.

  • v -> (Optional) An array of Numeric objects.

Returns:

  • The squared value of the euclidean norm of u or of the euclidean distance between u and v.

Raises:

  • ArgumentError -> The sizes of u and v don't match.

# File lib/measurable/euclidean.rb, line 47
def euclidean_squared(u, v = nil)
  # If the second argument is nil, the method should return the norm of
  # vector u. For this, we need the distance between u and the origin.
  if v.nil?
    v = Array.new(u.size, 0)
  end

  # TODO: Change this to a more specific, custom-made exception.
  raise ArgumentError if u.size != v.size

  u.zip(v).reduce(0.0) do |acc, ary|
    acc += (ary[0] - ary[-1]) ** 2
  end
end