def run(genes, norm_inputs, en=1): env = Environment(experiment_name=experiment_name, playermode="ai", player_controller=player_0(normalize=norm_inputs), speed="fastest", enemymode="static", level=2, randomini="no", enemies=[en]) return env.play(genes)
# Load solution and specify values bsol = np.loadtxt( experiment_name + '/Solution1.txt' ) # txt file with best solution for 1 enemy with 1 EA for a specific run #print(bsol) enemy_nr = 1 # emeny where the solution is created for EA_name = "EA1" # EA that is used to create solution run_nr = 1 # 1 to 10 df = pd.DataFrame(columns=[ "Enemy", "Algorithm", "Run", "Repetition", "Energy enemy", "Enegy player" ]) # Environment n_hidden_neurons = 10 env = Environment(experiment_name=experiment_name, enemies=[enemy_nr], playermode="ai", player_controller=player_controller(n_hidden_neurons), enemymode="static", level=2, speed="fastest") # run 5 times and add to df for i in range(0, 5): f, p, e, t = env.play(pcont=bsol) df.loc[i, ] = [enemy_nr, EA_name, run_nr, i + 1, e, p] # write data to file print(df) df.to_csv("df_boxplot.csv")