Rounding methods
Stochastic rounding provides a mechanism to eliminate accumulated roundoff error in the presence of a distribution where for individual samples, the roundoff error is skewed. This is typically caused by small values.
One drawback to stochastic rounding is the output is non-deterministic, but this can be avoided by providing a custom deterministic generator, or invoking providing the random number generator with a fixed seed.
r = random.Random()
r.seed(123)
sr = StochasticRound(precision=0, random_generator=r)