  A novel class of algorithms for restoring a function from a random sample is
based on the concept of weak convergence, borrows algorithmic solutions from
the Optimal Jet Finder (hep-ph/0301185), offers a considerable algorithmic
flexibility, is applicable to non-positive functions, is insensitive to the
choice of coordinate axes. A first implementation demonstrates feasibility of
the approach.
