(self, input_sample: np.ndarray, num_samples: int,
                                 num_params: int, k_choices: int,
                                 num_groups: int=None)
return maximum_combo
Use brute force method to find most distant trajectories

        Parameters
        ----------
        input_sample : numpy.ndarray
        num_samples : int
            The number of samples to generate
        num_params : int
            The number of parameters
        k_choices : int
            The number of optimal trajectories
        num_groups : int, default=None
            The number of groups

        Returns
        -------
        list
Use brute force method to find most distant trajectories
Use brute force method to find most distant trajectories
def brute_force_most_distant(self, input_sample: np.ndarray, num_samples: int,
                                 num_params: int, k_choices: int,
                                 num_groups: int=None) -> List:
        """Use brute force method to find most distant trajectories

        Parameters
        ----------
        input_sample : numpy.ndarray
        num_samples : int
            The number of samples to generate
        num_params : int
            The number of parameters
        k_choices : int
            The number of optimal trajectories
        num_groups : int, default=None
            The number of groups

        Returns
        -------
        list
        """
        scores = self.find_most_distant(input_sample,
                                        num_samples,
                                        num_params,
                                        k_choices,
                                        num_groups)

        maximum_combo = self.find_maximum(scores, num_samples, k_choices)

        return maximum_combo
def brute_force_most_distant ( self , input_sample : np . ndarray , num_samples : int , num_params : int , k_choices : int , num_groups : int = None ) -> List : scores = self . find_most_distant ( input_sample , num_samples , num_params , k_choices , num_groups ) maximum_combo = self . find_maximum ( scores , num_samples , k_choices ) return maximum_combo