

def get_most_separated_from_two_elements(self, first, second):
    '\n        Gets the element which distance to two elements is maximum.\n\n        @param first: First element to check against.\n        @param second: Second element to check against.\n\n        @return: A dictionary with the number of element and the\n        '
    max_s = {
        'element': 0,
        'mean_value': 0,
        'value': 0,
    }
    for i in range(self.distance_matrix.row_length):
        my_mean = numpy.mean([max_s.distance_matrix[(i, first)], self.distance_matrix[(i, second)]])
        if (my_mean > max_s['mean_value']):
            max_s['element'] = i
            max_s['mean_value'] = my_mean
            max_s['value'] = numpy.max([self.distance_matrix[(i, first)], self.distance_matrix[(i, second)]])
    return max_s

dataset/ETHPy150Open victor-gil-sepulveda/pyProCT/pyproct/clustering/algorithms/gromos/parametersGeneration.py ParametersGenerator.get_most_separated_from_two_elements/VarMisuse@58/169 `self`->`max_s`