def sample()

in level_replay/level_sampler.py [0:0]

• 24 lines of code
• 11 McCabe index (conditional complexity)

    def sample(self, strategy=None):
        if not strategy:
            strategy = self.strategy

        if strategy == 'random':
            seed_idx = np.random.choice(range((len(self.seeds))))
            seed = self.seeds[seed_idx]
            return int(seed)

        if strategy == 'sequential':
            seed_idx = self.next_seed_index
            self.next_seed_index = (self.next_seed_index + 1) % len(self.seeds)
            seed = self.seeds[seed_idx]
            return int(seed)

        num_unseen = (self.unseen_seed_weights > 0).sum()
        proportion_seen = (len(self.seeds) - num_unseen)/len(self.seeds)

        if self.replay_schedule == 'fixed':
            if proportion_seen >= self.rho: 
                # Sample replay level with fixed prob = 1 - nu OR if all levels seen
                if np.random.rand() > self.nu or not proportion_seen < 1.0:
                    return self._sample_replay_level()

            # Otherwise, sample a new level
            return self._sample_unseen_level()

        else: # Default to proportionate schedule
            if proportion_seen >= self.rho and np.random.rand() < proportion_seen:
                return self._sample_replay_level()
            else:
                return self._sample_unseen_level()