module Measurable::Euclidean
Public Instance Methods
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 betweenu
andv
.
Raises:
-
ArgumentError
-> The sizes ofu
andv
don't match.
# File lib/measurable/euclidean.rb, line 21 def euclidean(u, v = nil) Math.sqrt(self.euclidean_squared(u, v)) end
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 betweenu
andv
.
Raises:
-
ArgumentError
-> The sizes ofu
andv
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