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8697ae6 | 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 67 68 69 70 | """Tests for reward and final score computation."""
import pytest
from hr_env.server.scoring import compute_final_score, compute_quarterly_reward
class TestQuarterlyReward:
def test_positive_for_improvement(self):
prev = {"hcva": 100, "hcroi": 1.5, "qips": {"composite": 0.6}, "five_indexes": {"cost": -0.05, "quality": 0.1, "human_reactions": 0.05, "quantity": 0.02}}
curr = {"hcva": 110, "hcroi": 1.6, "qips": {"composite": 0.65}, "five_indexes": {"cost": -0.03, "quality": 0.12, "human_reactions": 0.08, "quantity": 0.03}}
reward = compute_quarterly_reward(curr, prev)
assert reward > 0, f"Reward should be positive for improvement, got {reward}"
def test_negative_for_decline(self):
prev = {"hcva": 110, "hcroi": 1.6, "qips": {"composite": 0.65}, "five_indexes": {"cost": 0.0, "quality": 0.0, "human_reactions": 0.0, "quantity": 0.0}}
curr = {"hcva": 90, "hcroi": 1.3, "qips": {"composite": 0.55}, "five_indexes": {"cost": 0.1, "quality": -0.1, "human_reactions": -0.1, "quantity": -0.05}}
reward = compute_quarterly_reward(curr, prev)
assert reward < 0, f"Reward should be negative for decline, got {reward}"
def test_near_zero_for_no_change(self):
metrics = {"hcva": 100, "hcroi": 1.5, "qips": {"composite": 0.6}, "five_indexes": {"cost": 0.0, "quality": 0.0, "human_reactions": 0.0, "quantity": 0.0}}
reward = compute_quarterly_reward(metrics, metrics)
assert abs(reward) < 0.1, f"Reward should be near zero, got {reward}"
class TestFinalScore:
def test_bounded_zero_one(self):
history = [
{"hcva": 100, "hcroi": 1.5, "qips": {"composite": 0.6}, "five_indexes": {"cost": 0, "quality": 0, "human_reactions": 0}, "employee_value": 0.5, "profit": 1000000},
{"hcva": 105, "hcroi": 1.55, "qips": {"composite": 0.62}, "five_indexes": {"cost": -0.02, "quality": 0.05, "human_reactions": 0.03}, "employee_value": 0.52, "profit": 1100000},
{"hcva": 110, "hcroi": 1.6, "qips": {"composite": 0.64}, "five_indexes": {"cost": -0.01, "quality": 0.03, "human_reactions": 0.02}, "employee_value": 0.55, "profit": 1200000},
]
score = compute_final_score(history)
assert 0 <= score <= 1.0, f"Score {score} out of [0, 1] range"
def test_higher_for_improvement_trajectory(self):
improving = [
{"hcva": 100, "hcroi": 1.5, "qips": {"composite": 0.5}, "five_indexes": {"cost": 0, "quality": 0, "human_reactions": 0}, "employee_value": 0.4, "profit": 500000},
{"hcva": 120, "hcroi": 1.7, "qips": {"composite": 0.6}, "five_indexes": {"cost": -0.05, "quality": 0.1, "human_reactions": 0.1}, "employee_value": 0.5, "profit": 700000},
{"hcva": 140, "hcroi": 1.9, "qips": {"composite": 0.7}, "five_indexes": {"cost": -0.03, "quality": 0.08, "human_reactions": 0.05}, "employee_value": 0.6, "profit": 900000},
]
declining = [
{"hcva": 140, "hcroi": 1.9, "qips": {"composite": 0.7}, "five_indexes": {"cost": 0, "quality": 0, "human_reactions": 0}, "employee_value": 0.6, "profit": 900000},
{"hcva": 120, "hcroi": 1.5, "qips": {"composite": 0.55}, "five_indexes": {"cost": 0.1, "quality": -0.1, "human_reactions": -0.1}, "employee_value": 0.45, "profit": 500000},
{"hcva": 100, "hcroi": 1.2, "qips": {"composite": 0.4}, "five_indexes": {"cost": 0.15, "quality": -0.15, "human_reactions": -0.12}, "employee_value": 0.35, "profit": 200000},
]
score_improving = compute_final_score(improving)
score_declining = compute_final_score(declining)
assert score_improving > score_declining
def test_empty_history(self):
score = compute_final_score([])
assert score == 0.0
def test_single_quarter(self):
score = compute_final_score([{"hcva": 100}])
assert score == 0.0
def test_profitable_scores_higher(self):
profitable = [
{"hcva": 100, "hcroi": 1.5, "qips": {"composite": 0.6}, "five_indexes": {"cost": 0, "quality": 0, "human_reactions": 0}, "employee_value": 0.5, "profit": 1000000},
{"hcva": 100, "hcroi": 1.5, "qips": {"composite": 0.6}, "five_indexes": {"cost": 0, "quality": 0, "human_reactions": 0}, "employee_value": 0.5, "profit": 1000000},
]
unprofitable = [
{"hcva": 100, "hcroi": 1.5, "qips": {"composite": 0.6}, "five_indexes": {"cost": 0, "quality": 0, "human_reactions": 0}, "employee_value": 0.5, "profit": -500000},
{"hcva": 100, "hcroi": 1.5, "qips": {"composite": 0.6}, "five_indexes": {"cost": 0, "quality": 0, "human_reactions": 0}, "employee_value": 0.5, "profit": -500000},
]
assert compute_final_score(profitable) > compute_final_score(unprofitable)
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