Finding the entropy for Ruby's random method as a measure of it's randomness

rb_rand_entropy.rb

def rb_rand_entropy(num_trials)
	a = Array.new(num_trials) {rand(100)}
	p = []
	0.upto(99) do |i|
		p[i] = a.count(i) / num_trials.to_f
	end

	return p.map {|c| -c * Math.log(c)}.reduce(:+)
end

1.upto(7) do |t|
	puts [Math.exp(rb_rand_entropy(10 ** t)), t].inspect
end

# Returns this (n' is the estimated value of the parameter n, should be 100)\
# The RHS is (n', num_samples)
# => NaN
# => NaN
# => 4.557993577783632 # => (n', num_samples) = (95.3918912807, 1_000)
# => 4.600420244466219 # => (n', num_samples) = (99.5261321610, 10_000)
# => 4.604752839404147 # => (n', num_samples) = (99.9582740493, 100_000)
# => 4.605116270790972 # => (n', num_samples) = (99.9946086256, 1_000_000)
# => 4.605166004190653 # => (n', num_samples) = (99.9995818211, 10_000_000)
#