def solve_classical()

in src/qbsolv_community.py [0:0]

• 11 lines of code
• 1 McCabe index (conditional complexity)

    def solve_classical(self, num_comm):
        """
        Call QUBO classical solver for community detection

        :param num_comm: int, number of communities to solve for
        :return: dict, two dictionaries for graph's community results and QBSolv reponse results
        """
        t0 = time.time()

        q_dict = create_qubo_dict(self.graph, num_comm, self.alpha)
    
        # execute optimization task using QBSolv classical (run on your local notebook instance) 
        response_classical = QBSolv().sample_qubo(
            q_dict, num_repeats=self.num_repeats, solver_limit=self.solver_limit, seed=self.seed
        )
        print(f"Mode: Classical, time spent is {round(time.time()-t0, 2)} seconds for {self.num_repeats} repetitions")
        print(response_classical)
        
        # extract the best solution that has the lowest energy
        sample_classical = np.array(list(response_classical.first.sample.values()))
        comm_classical = qbsolv_response_to_community(self.graph, sample_classical, num_comm)
        
        return comm_classical, response_classical