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")
