def abspath(self):
        try:
            return self.cache_abspath
        except:
            pass
        # think twice before touching this (performance + complexity + correctness)
        if not self.parent:
            val = os.sep == '/' and os.sep or ''
        elif not self.parent.name:
            # drive letter for win32
            val = (os.sep == '/' and os.sep or '') + self.name
        else:
            val = self.parent.abspath() + os.sep + self.name

        self.cache_abspath = val
        return val
Returns loss on X with respect to list of triplets S: 1/len(S) \sum_{q in S} loss(X,q).
dataset/ETHPy150Open cournape/Bento/bento/core/node.py/Node.abspath--crossover with--dataset/ETHPy150Open nextml/NEXT/next/apps/PoolBasedTripletMDS/algs/RandomSampling/utilsMDS.py/getLoss