def build_normalised_scores(self):
        normalised_scores = [
            [[] for rep in range(self.nrepetitions)] for _ in
            range(self.nplayers)]

        # Getting list of all per turn scores for each player for each rep
        for rep, inter_dict in enumerate(self.interactions):
            for index_pair, interactions in inter_dict.items():
                if index_pair[0] != index_pair[1]:  # Ignore self interactions
                    scores_per_turn = iu.compute_final_score_per_turn(interactions)
                    for player in range(2):
                        player_index = index_pair[player]
                        score_per_turn = scores_per_turn[player]
                        normalised_scores[player_index][rep].append(score_per_turn)

        # Obtaining mean scores and overwriting corresponding entry in
        # normalised scores
        for i, rep in enumerate(normalised_scores):
            for j, player_scores in enumerate(rep):
                normalised_scores[i][j] = mean(player_scores)

        return normalised_scores
Returns:
dataset/ETHPy150Open Axelrod-Python/Axelrod/axelrod/result_set.py/ResultSet.build_normalised_scores