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20bc5e4 | 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 54 55 56 57 58 59 60 61 62 63 64 65 66 | import sys
sys.path.insert(0, ".")
import pytest
import math
from src.pll_sim import SRFPLLSimulator, OMEGA0
from src.env import PLLAttackEnv
from src.models import Action
from src.attacks import AttackGenerator, sample_sinusoidal_params
import numpy as np
DUMMY_ACTION = Action(
attack_detected=False,
attack_type=0,
confidence=0.5,
protective_action=0
)
def test_episode_terminates_at_500():
"""Episode must terminate with done=True at step 500."""
env = PLLAttackEnv()
env.reset(task_id=0, seed=42)
done = False
steps = 0
while not done:
_, _, done, _ = env.step(DUMMY_ACTION)
steps += 1
assert steps == 500, f"Episode ended at step {steps}, expected 500"
def test_all_tasks_reset():
"""All three tasks must reset without error."""
env = PLLAttackEnv()
for task_id in range(3):
obs = env.reset(task_id=task_id, seed=42)
assert obs.task_id == task_id
assert obs.step == 0
assert len(obs.vq_window) == 20
def test_oracle_agent_nonzero_reward():
"""An oracle agent should accumulate positive reward."""
env = PLLAttackEnv()
env.reset(task_id=0, seed=42)
total_reward = 0.0
done = False
while not done:
action = Action(
attack_detected=env.attack_active,
attack_type=env.true_attack_type if env.attack_active else 0,
confidence=1.0,
protective_action=0
)
_, reward, done, _ = env.step(action)
total_reward += reward.total
assert total_reward > 0, f"Oracle agent got non-positive reward: {total_reward}"
def test_reward_bounds():
"""Reward total must stay within [-2.5, 1.5] per step."""
env = PLLAttackEnv()
env.reset(task_id=2, seed=42)
done = False
while not done:
_, reward, done, _ = env.step(DUMMY_ACTION)
assert -2.5 <= reward.total <= 1.5, (
f"Reward out of bounds: {reward.total}"
)
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