def build_normalised_cooperation(self):
        plist = list(range(self.nplayers))
        normalised_cooperations = [[0 for opponent in plist] for player in plist]

        for player in plist:
            for opponent in plist:
                coop_counts = []
                for rep in self.interactions:

                    if (player, opponent) in rep:
                        interactions = rep[(player, opponent)]
                        coop_counts.append(iu.compute_normalised_cooperation(interactions)[0])

                    if (opponent, player) in rep:
                        interactions = rep[(opponent, player)]
                        coop_counts.append(iu.compute_normalised_cooperation(interactions)[1])

                    if ((player, opponent) not in rep) and ((opponent, player) not in rep):
                        coop_counts.append(0)

                    # Mean over all reps:
                    normalised_cooperations[player][opponent] = mean(coop_counts)
        return normalised_cooperations
Creates tempfile, wildcard searches for all archive logs, then uses bz2 module
dataset/ETHPy150Open Axelrod-Python/Axelrod/axelrod/result_set.py/ResultSet.build_normalised_cooperation--crossover with--dataset/ETHPy150Open macadmins/sashay/sashay.py/join_bzipped_logs