def split(self, count):
        """Split the learner into multiple learners.

        Splits self.networks into `count` parts. This is similar to MPI's
        scatter functionality.
    
        """

        nets = list(self.networks)
        numnets = len(nets)
        netspertask = numnets/count

        # divide list into parts
        indices = [[i,i+netspertask] for i in xrange(0,numnets,netspertask)]
        if count > len(indices):
            indices.pop(-1)
            indices[-1][1] = numnets-1

        return [ListLearner(self.data, self.prior, nets[i:j])for i,j in indices]
dataset/ETHPy150Open abhik/pebl/src/pebl/learner/exhaustive.py/ListLearner.split/swapped operands of `>`