assert NUMBER_OF_SAMPLES % MAX_GAME_SIZE == 0,\
"The number of samples must be evenly divisible by max game size."
# Generate the datasets
for i in range(len(player_number)):
for j in range(int(NUMBER_OF_SAMPLES / MAX_GAME_SIZE)):
# Print a message
print('+++Starting to generate a dataset of games with size ' + str(PURE_STRATEGIES_PER_PLAYER[i]) + ' - number: ' + str(j + 1))
# Set the subfolder to save the data in
save_subfolder = str(DATASET_NUMBER) + "/" + str(PURE_STRATEGIES_PER_PLAYER[i]).rstrip(")]").lstrip("[(").replace(",", "x").replace(" ", "") + "/"
# Run the dataset generator
Dataset_Generator.multi_process_generator(games_dataset_name=games_dataset_name[i] + "_" + str(j),
equilibria_dataset_name=equilibria_dataset_name[i] + "_" + str(j),
number_of_samples=MAX_GAME_SIZE,
max_equilibria_per_game=MAXIMUM_EQUILIBRIA_PER_GAME,
player_number=player_number[i],
strategies_per_player=PURE_STRATEGIES_PER_PLAYER[i],
discard_non_mixed_strategy_games=DISCARD_NON_MIXED_STRATEGY_GAMES,
filter_pure_strategies=FILTER_PURE_STRATEGIES,
discard_single_equilibrium_games=DISCARD_SINGLE_EQUILIBRIUM_GAMES,
use_gambit=USE_GAMBIT,
cpu_cores=CPU_CORES,
timeout_per_sample=TIMEOUT_PER_SAMPLE,
game_type="Random",
save_subfolder=save_subfolder)
print('***Finished generating ' + str(NUMBER_OF_SAMPLES) + ' samples of size ' + str(PURE_STRATEGIES_PER_PLAYER[i]) + ' - number: ' + str(j + 1) + '\n')
