+ sum += (value.to_f - avg).pow(2.0)
+ end
+ return (sum / map.length.to_f).sqrt
+ end
+
+ # The information entropy (Shannon entropy) of the elements in the counter (in bits).
+ fun entropy: Float
+ do
+ var res = 0.0
+ var sum = self.sum.to_f
+ for k, v in self do
+ var f = v.to_f / sum
+ res = res - f * f.log_base(2.0)
+ end
+ return res
+ end
+
+ # Prints the content of the counter along with statistics
+ #
+ # Content is printed in order (if available) from lowest to highest on the keys.
+ # Else, it is printed as-is
+ fun print_content do
+ var a = keys.to_a
+ if a isa Array[Comparable] then default_comparator.sort(a)
+ var subtotal = 0
+ for i in a do
+ subtotal += self[i]
+ printn("* ", i or else "null", " = ", self[i], " => occurences ", self[i].to_f / sum.to_f * 100.0, "%, cumulative ", subtotal.to_f / sum.to_f * 100.0, "% \n")