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36131f5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | import numpy as np
from artwork_bandit.bandit.linucb import LinUCBArm, LinUCBBandit
from artwork_bandit.bandit.thompson import ThompsonBandit
def test_linucb_score_and_update():
d=10
arm = LinUCBArm(d=d, alpha=0.5)
ctx = np.ones(d)
s = arm.score(ctx)
assert isinstance(s, float)
A0 = arm.A.copy()
b0 = arm.b.copy()
arm.update(ctx, 1.0)
assert not np.allclose(arm.A, A0)
assert not np.allclose(arm.b, b0)
def test_linucb_bandit_select():
arms = ['a','b','c']
d=5
bandit = LinUCBBandit(arms, d=d, alpha=1.0)
contexts = {a: np.ones(d) * i for i,a in enumerate(arms, start=1)}
chosen = bandit.select(contexts)
assert chosen in arms
def test_linucb_exploit_after_updates():
arms = ['a','b','c']
d=5
bandit = LinUCBBandit(arms, d=d, alpha=0.1)
ctx = np.ones(d)
# reward arm 'b' heavily
for _ in range(100):
bandit.update('b', ctx, 1.0)
counts = {a:0 for a in arms}
for _ in range(100):
chosen = bandit.select({a:ctx for a in arms})
counts[chosen]+=1
assert counts['b'] > 80
def test_thompson_select():
arms = [f'a{i}' for i in range(4)]
t = ThompsonBandit(arms)
chosen = t.select(arms)
assert chosen in arms
def test_linucb_serialization_roundtrip():
d=3
arm = LinUCBArm(d=d, alpha=1.0)
arm.update(np.ones(d), 1.0)
data = arm.to_dict()
arm2 = LinUCBArm.from_dict('x', d, data, alpha=1.0)
assert np.allclose(arm.A, arm2.A)
assert np.allclose(arm.b, arm2.b)
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