def compute_metrics(strategies, noise=0):
results = run_tournament("tournament", strategies, noise=noise)
rows = []
for i in range(len(results.players)):
row = [str(results.players[i]), numpy.mean(results.normalised_scores[i]), numpy.mean(results.normalised_cooperation[i]), results.good_partner_rating[i], results.eigenjesus_rating[i], results.eigenmoses_rating[i]]
rows.append(row)
return rows
def compute_metrics(strategies, noise=0):
results = run_tournament("tournament", strategies, noise=noise)
rows = []
for i in range(len(results.players)):
row = [
str(results.players[i]),
numpy.mean(results.normalised_scores[i]),
numpy.mean(results.normalised_cooperation[i]),
results.good_partner_rating[i],
results.eigenjesus_rating[i],
results.eigenmoses_rating[i],
]
rows.append(row)
return rows
def tournament_data(players, turns=200, repetitions=100):
"""
Run tournaments with repetition and record the following:
mean score
mean wins
wins deviation
score deviation
"""
results = run_tournament("--", players, turns=turns, repetitions=repetitions)
score_data = results.normalised_scores
win_data = results.wins
mean_scores = [numpy.mean(s) for s in score_data]
std_scores = [numpy.std(s) for s in score_data]
mean_wins = [numpy.mean(w) for w in win_data]
std_wins = [numpy.std(w) for w in win_data]
return (mean_scores, std_scores, mean_wins, std_wins)
def tournament_data(players, turns=200, repetitions=100):
"""
Run tournaments with repetition and record the following:
mean score
mean wins
wins deviation
score deviation
"""
results = run_tournament("--",
players,
turns=turns,
repetitions=repetitions)
score_data = results.normalised_scores
win_data = results.wins
mean_scores = [numpy.mean(s) for s in score_data]
std_scores = [numpy.std(s) for s in score_data]
mean_wins = [numpy.mean(w) for w in win_data]
std_wins = [numpy.std(w) for w in win_data]
return (mean_scores, std_scores, mean_wins, std_wins)
