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Unit tests for FairnessManagerAgent.
Tests Gini calculation, metric computation, and ACCEPT/REOPTIMIZE decision logic.
"""
import pytest
from app.services.fairness_manager_agent import FairnessManagerAgent
from app.schemas.agent_schemas import (
AllocationItem,
FairnessThresholds,
RoutePlanResult,
)
from uuid import uuid4
def create_mock_plan_result(efforts: list[float]) -> RoutePlanResult:
"""Create a mock RoutePlanResult from effort values."""
allocation = []
per_driver_effort = {}
for i, effort in enumerate(efforts):
driver_id = uuid4()
route_id = uuid4()
allocation.append(AllocationItem(
driver_id=driver_id,
route_id=route_id,
effort=effort,
))
per_driver_effort[str(driver_id)] = effort
return RoutePlanResult(
allocation=allocation,
total_effort=sum(efforts),
avg_effort=sum(efforts) / len(efforts) if efforts else 0.0,
per_driver_effort=per_driver_effort,
proposal_number=1,
)
class TestFairnessManagerAgent:
"""Test suite for FairnessManagerAgent."""
def test_gini_perfect_equality(self):
"""Test Gini index for perfectly equal distribution."""
agent = FairnessManagerAgent()
# All drivers have same effort
plan = create_mock_plan_result([50.0, 50.0, 50.0, 50.0])
result = agent.check(plan)
assert result.metrics.gini_index == 0.0, "Perfect equality should have Gini = 0"
def test_gini_inequality(self):
"""Test Gini index for unequal distribution."""
agent = FairnessManagerAgent()
# Unequal efforts
plan = create_mock_plan_result([10.0, 20.0, 30.0, 100.0])
result = agent.check(plan)
assert result.metrics.gini_index > 0.0, "Unequal distribution should have Gini > 0"
assert result.metrics.gini_index <= 1.0, "Gini should not exceed 1"
def test_std_dev_calculation(self):
"""Test standard deviation calculation."""
agent = FairnessManagerAgent()
# Known values for easy verification
plan = create_mock_plan_result([60.0, 60.0, 60.0]) # Zero std dev
result = agent.check(plan)
assert result.metrics.std_dev == 0.0, "Equal values should have std_dev = 0"
# Varied values
plan2 = create_mock_plan_result([50.0, 60.0, 70.0])
result2 = agent.check(plan2)
assert result2.metrics.std_dev > 0.0, "Varied values should have std_dev > 0"
def test_max_gap_calculation(self):
"""Test max gap (max - min) calculation."""
agent = FairnessManagerAgent()
plan = create_mock_plan_result([30.0, 50.0, 80.0])
result = agent.check(plan)
expected_gap = 80.0 - 30.0
assert result.metrics.max_gap == expected_gap
assert result.metrics.min_effort == 30.0
assert result.metrics.max_effort == 80.0
def test_accept_when_within_thresholds(self):
"""Test ACCEPT status when all thresholds met."""
agent = FairnessManagerAgent(
thresholds=FairnessThresholds(
gini_threshold=0.5,
stddev_threshold=50.0,
max_gap_threshold=50.0,
)
)
# Equal-ish distribution
plan = create_mock_plan_result([55.0, 60.0, 65.0])
result = agent.check(plan)
assert result.status == "ACCEPT"
assert result.recommendations is None
def test_reoptimize_when_gini_exceeds_threshold(self):
"""Test REOPTIMIZE status when Gini exceeds threshold."""
agent = FairnessManagerAgent(
thresholds=FairnessThresholds(
gini_threshold=0.1, # Very strict
stddev_threshold=100.0,
max_gap_threshold=100.0,
)
)
# Unequal distribution
plan = create_mock_plan_result([10.0, 50.0, 90.0])
result = agent.check(plan)
assert result.status == "REOPTIMIZE"
assert result.recommendations is not None
def test_reoptimize_when_stddev_exceeds_threshold(self):
"""Test REOPTIMIZE status when std_dev exceeds threshold."""
agent = FairnessManagerAgent(
thresholds=FairnessThresholds(
gini_threshold=1.0,
stddev_threshold=5.0, # Very strict
max_gap_threshold=100.0,
)
)
plan = create_mock_plan_result([30.0, 50.0, 70.0])
result = agent.check(plan)
assert result.status == "REOPTIMIZE"
def test_reoptimize_when_max_gap_exceeds_threshold(self):
"""Test REOPTIMIZE status when max_gap exceeds threshold."""
agent = FairnessManagerAgent(
thresholds=FairnessThresholds(
gini_threshold=1.0,
stddev_threshold=100.0,
max_gap_threshold=10.0, # Very strict
)
)
plan = create_mock_plan_result([40.0, 50.0, 80.0]) # Gap = 40
result = agent.check(plan)
assert result.status == "REOPTIMIZE"
def test_recommendations_identify_high_effort_drivers(self):
"""Test that recommendations identify high-effort drivers."""
agent = FairnessManagerAgent(
thresholds=FairnessThresholds(
gini_threshold=0.1,
stddev_threshold=5.0,
max_gap_threshold=10.0,
)
)
plan = create_mock_plan_result([50.0, 50.0, 50.0, 100.0]) # One outlier
result = agent.check(plan)
assert result.status == "REOPTIMIZE"
assert result.recommendations is not None
assert len(result.recommendations.high_effort_driver_ids) > 0
assert result.recommendations.penalty_factor >= 1.0
def test_outlier_count(self):
"""Test outlier counting (drivers above avg + 2*std_dev)."""
agent = FairnessManagerAgent()
# Create distribution with clear outlier
# [10] * 8 + [100]: Mean=20, Std=30, Threshold=20+2*30=80. 100 > 80.
plan = create_mock_plan_result([10.0] * 8 + [100.0])
result = agent.check(plan)
assert result.metrics.outlier_count >= 1
def test_empty_plan(self):
"""Test handling of empty plan."""
agent = FairnessManagerAgent()
plan = create_mock_plan_result([])
result = agent.check(plan)
assert result.status == "ACCEPT"
assert result.metrics.gini_index == 0.0
assert result.metrics.std_dev == 0.0
def test_single_driver(self):
"""Test handling of single driver."""
agent = FairnessManagerAgent()
plan = create_mock_plan_result([75.0])
result = agent.check(plan)
assert result.status == "ACCEPT"
assert result.metrics.gini_index == 0.0
assert result.metrics.std_dev == 0.0
assert result.metrics.max_gap == 0.0
def test_thresholds_included_in_result(self):
"""Test that used thresholds are included in result."""
thresholds = FairnessThresholds(
gini_threshold=0.25,
stddev_threshold=20.0,
max_gap_threshold=30.0,
)
agent = FairnessManagerAgent(thresholds=thresholds)
plan = create_mock_plan_result([50.0, 60.0])
result = agent.check(plan)
assert result.thresholds_used["gini_threshold"] == 0.25
assert result.thresholds_used["stddev_threshold"] == 20.0
assert result.thresholds_used["max_gap_threshold"] == 30.0
def test_snapshot_generation(self):
"""Test input/output snapshot generation."""
agent = FairnessManagerAgent()
plan = create_mock_plan_result([40.0, 50.0, 60.0])
input_snapshot = agent.get_input_snapshot(plan)
assert "proposal_number" in input_snapshot
assert "num_drivers" in input_snapshot
result = agent.check(plan)
output_snapshot = agent.get_output_snapshot(result)
assert "status" in output_snapshot
assert "gini_index" in output_snapshot
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