pygsti.extras.drift.signal.standardizer

standardizer(x, null_hypothesis=None, counts=1)

Maps the vector x over [0, counts] as

x - > (x - counts * null_hypothesis) / sqrt(counts * null_hypothesis * (1-null_hypothesis)),

where the arithmetic is element-wise, and null_hypothesis is a vector in (0,1). If null_hypothesis is None it is set to the mean of x. If that mean is 0 or 1 then None is returned.