Generate an initial sample for the Markov chain. This function will return a list 
        containing integer representations of each candidate in order of their rank in the current 
        vote, from first to last. The list will be a complete strict ordering over the candidates.
        Initially, we rank the candidates in random order.

        ivar: dict<int,<dict,<int,int>>> wmg: A two-dimensional dictionary that associates integer
            representations of each pair of candidates, cand1 and cand2, with the number of times
            cand1 is ranked above cand2 minus the number of times cand2 is ranked above cand1. The
            dictionary represents a weighted majority graph for an election.

def getInitialSample(self, wmg):
        """
        Generate an initial sample for the Markov chain. This function will return a list 
        containing integer representations of each candidate in order of their rank in the current 
        vote, from first to last. The list will be a complete strict ordering over the candidates.
        Initially, we rank the candidates in random order.

        ivar: dict<int,<dict,<int,int>>> wmg: A two-dimensional dictionary that associates integer
            representations of each pair of candidates, cand1 and cand2, with the number of times
            cand1 is ranked above cand2 minus the number of times cand2 is ranked above cand1. The
            dictionary represents a weighted majority graph for an election.
        """
        
        V = copy.deepcopy(wmg.keys())
        random.shuffle(V)
        return V