  In [3], algorithms to compute the density of the distance to a random
variable uniformly distributed in (a) a ball, (b) a disk, (c) a line segment,
or (d) a polygone were introduced. For case (d), the algorithm, based on
Green's theorem, has complexity nlog(n) where n is the number of vertices of
the polygone. In this paper, we present for case (d) another algorithm with the
same complexity, based on a triangulation of the polygone. We also describe an
open source library providing this algorithm as well as the algorithms from
[3].
  [3] V. Guigues, Computation of the cumulative distribution function of the
Euclidean distance between a point and a random variable uniformly distributed
in disks, balls, or polyhedrons and application to Probabilistic Seismic Hazard
Analysis, arXiv, available at arXiv:1809.02007, 2015.

Computational Geometry;Probability