  The wrapped normal distribution arises when a the density of a
one-dimensional normal distribution is wrapped around the circle infinitely
many times. At first look, evaluation of its probability density function
appears tedious as an infinite series is involved. In this paper, we
investigate the evaluation of two truncated series representations. As one
representation performs well for small uncertainties whereas the other performs
well for large uncertainties, we show that in all cases a small number of
summands is sufficient to achieve high accuracy.
