height = 36
N_cust = 120
pixel_ratio = 20
num_agents = 12
theme = "cluster"
strategy = "Random_test_4"
steps = 520
RUNS = 65
strategies = [0, 0.25, 0.5, 0.75, 1]
adaptive = True
cust_d, score_d, hapiness_d, hist_d, strategy_d, dict2 = [], [], [], [], [], []
for run in range(RUNS):
print("RUN ", run)
park = Themepark(num_agents, N_cust, width, height, strategy, theme, steps,
strategies, adaptive)
for i in range(steps + 1):
print("step", i)
park.step()
print("Number of run:", run)
try:
cust = pickle.load(open("data/customers.p", 'rb'))
score = pickle.load(open("data/park_score.p", "rb"))
hapiness = pickle.load(open("data/hapiness.p", "rb"))
hist = pickle.load(open("data/cust_history.p", 'rb'))
strategy_hist = pickle.load(open("data/strategy_history.p", 'rb'))
dict2_data = pickle.load(open("data/eff_score_history.p", 'rb'))
except:
strategies = [0, 0.25, 0.5, 0.75, 1, "Random"]
N_cust = 120
num_agents = 12
steps = 520
RUNS = 65
cust_d, score_d, hapiness_d, hist_d, strat_d, score_ed = [], [], [], [], [], []
for j in range(RUNS):
print()
print("RUN ", j)
print()
park = Themepark(num_agents, N_cust, width, height, strategy, theme, steps,
None)
for i in range(steps + 1):
print("step", i)
park.step()
cust = pickle.load(open("../data/customers.p", 'rb'))
score = pickle.load(open("../data/park_score.p", "rb"))
hapiness = pickle.load(open("../data/hapiness.p", "rb"))
hist = pickle.load(open("../data/cust_history.p", 'rb'))
strategy_hist = pickle.load(open("../data/stategy_history.p", 'rb'))
cust_d.append(cust)
score_d.append(score)
hapiness_d.append(hapiness)
hist_d.append(hist)