total_variation_distance¶
-
forest.benchmarking.distance_measures.
total_variation_distance
(P: numpy.ndarray, Q: numpy.ndarray) → float¶ Computes the total variation distance between two (classical) probability measures P(x) and Q(x).
When x is a finite alphabet then the definition is
\[tvd(P,Q) = (1/2) \sum_x |P(x) - Q(x)|\]where tvd(P,Q) is in [0, 1]. There is an alternate definition for non-finite alphabet measures involving a supremum.
Parameters: - P – Is a dim by 1 np.ndarray.
- Q – Is a dim by 1 np.ndarray.
Returns: total variation distance which is a scalar.