_do_selection.py

    arr = pop_df.to_numpy()
    split = np.split(
        arr[:, 2],
        np.unique(arr[:, [0, 1]], axis=0, return_index=True)[1][1:],
    )
    pos = 0
    for group in split:
        # minimizing operations on group_df gives >50% speedup
        genome_lookup = group
        tournament_rosters = np.random.randint(
            len(genome_lookup),
            size=(island_niche_size, tournament_size),
        )
        tournamnt_fitnesses = genome_lookup[tournament_rosters]
        winning_tournament_positions = tournamnt_fitnesses.argmax(1)
        winning_idxs = tournament_rosters[
            np.arange(len(tournament_rosters)),
            winning_tournament_positions,
        ] + pos
        assert len(winning_idxs) == island_niche_size
    
        pos += len(group)
        res.extend(winning_idxs)