# coding: utf-8
from src.minority_game import MinorityGameWithStrategyTable
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
if __name__ == "__main__":
# set agent num
agent_num = 201
# set round number from 10000 to 100000
round_num = 100000
depth = 3
strategy_num = 2
mean_list = []
stdd_list = []
# Run the game for different round number
game = MinorityGameWithStrategyTable(agent_num, round_num,depth,strategy_num)
mean_list,stdd_list = game.run_game()
# print result
print(mean_list)
print(stdd_list)
# plot mean
rounds = list(range(10000,110000,10000))
fig = plt.figure(figsize=(10, 4))
plt.plot(rounds,mean_list)
plt.subplots_adjust(left=0.1, right=0.9, top=0.9, bottom=0.2)
fig.suptitle('Mean Value')
plt.xlabel('Iteration number')
plt.ylabel('Average numbers of winners')
fig.savefig('ex3-2-S2-D3-mean.jpg')
import matplotlib.pyplot as plt
import seaborn as sns
if __name__ == "__main__":
# set agent num
agent_num = 201
# set round number from 10000 to 100000
round_num = 10000
depth_grid = range(3,11)
strategy_num = [3,4,8,16,32,64]
result = pd.DataFrame(columns = ["strategy_num","d","mean","std"])
# Run the game for different round number
i =0
for depth in depth_grid:
for sn in strategy_num:
game = MinorityGameWithStrategyTable(agent_num, round_num,depth,sn)
game.run_game()
mean,stdd = game.score_mean_std
result.loc[i] = [sn,depth,mean,stdd]
i+=1
g = sns.factorplot(x="d", y="mean", hue="strategy_num", data=result,
palette="YlGnBu_d", size=6, aspect=1.3)
plt.xlabel('Memory Size')
plt.ylabel('Average numbers of winners')
g.savefig("differerentSDmean")
g = sns.factorplot(x="d", y="std", hue="strategy_num", data=result,
palette="YlGnBu_d", size=6, aspect=1.3)
plt.xlabel('Memory Size')
plt.ylabel('winner number stdd')
# !/usr/bin/env python3 # coding: utf-8 from src.minority_game import MinorityGameWithStrategyTable game = MinorityGameWithStrategyTable(201, 50000, 3, 2,64) game.run_game() print(game.winner_for_diff_group())
import matplotlib.pyplot as plt
import seaborn as sns
if __name__ == "__main__":
# set agent num
agent_num = 201
# set round number from 10000 to 100000
round_num = 10000
depth_grid = range(3, 11)
strategy_num = [3, 4, 8, 16, 32, 64]
result = pd.DataFrame(columns=["strategy_num", "d", "mean", "std"])
# Run the game for different round number
i = 0
for depth in depth_grid:
for sn in strategy_num:
game = MinorityGameWithStrategyTable(agent_num, round_num, depth,
sn)
game.run_game()
mean, stdd = game.score_mean_std
result.loc[i] = [sn, depth, mean, stdd]
i += 1
g = sns.factorplot(x="d",
y="mean",
hue="strategy_num",
data=result,
palette="YlGnBu_d",
size=6,
aspect=1.3)
plt.xlabel('Memory Size')
plt.ylabel('Average numbers of winners')
g.savefig("differerentSDmean")