def get_parameters(self):
        run_parameters = []

        # (minpts, eps tuples)
        if "max" in self.parameters["clustering"]["algorithms"]["dbscan"]:
            max_eps_tries = self.parameters["clustering"]["algorithms"]["dbscan"]["max"]
        else:
            max_eps_tries = 10

        num_elements = self.distance_matrix.row_length
        klist = k_scale_gen(math.log(num_elements))
        buffer = numpy.empty(num_elements)
        kdist_matrix = k_dist(klist, buffer, self.distance_matrix)

        dbscan_param_pairs = dbscanTools.dbscan_param_space_search(self.parameters["clustering"]["evaluation"]["maximum_noise"],
                                                                   max_eps_tries,
                                                                   num_elements,
                                                                   klist,
                                                                   kdist_matrix) +\
                            zhou_adaptative_determination(kdist_matrix, self.distance_matrix)

        for (minpts, eps) in dbscan_param_pairs:
            run_parameter = ParametersGenerator.get_base_parameters()
            run_parameter["minpts"] = minpts
            run_parameter["eps"] = eps
            run_parameters.append(run_parameter)

        return run_parameters, []
Like L{buildAddress}, but with a different fixed address.
dataset/ETHPy150Open victor-gil-sepulveda/pyProCT/pyproct/clustering/algorithms/dbscan/parametersGeneration.py/ParametersGenerator.get_parameters--crossover with--dataset/ETHPy150Open nlloyd/SubliminalCollaborator/libs/twisted/internet/test/test_address.py/IPv4AddressTCPTestCase.buildDifferentAddress